Overview

Brought to you by YData

Dataset statistics

Number of variables68
Number of observations1926624
Missing cells64723914
Missing cells (%)49.4%
Total size in memory999.5 MiB
Average record size in memory544.0 B

Variable types

Text68

Dataset

DescriptionInvertebrate Zoology NMNH Extant Specimen Records (USNM) 0052489-241126133413365
URLhttps://doi.org/10.15468/hnhrg3

Alerts

institutionID has constant value "urn:lsid:biocol.org:col:34871" Constant
collectionID has constant value "urn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6" Constant
institutionCode has constant value "USNM" Constant
collectionCode has constant value "IZ" Constant
datasetName has constant value "NMNH Extant Biology" Constant
recordNumber has 1804854 (93.7%) missing values Missing
recordedBy has 764209 (39.7%) missing values Missing
sex has 1744537 (90.5%) missing values Missing
lifeStage has 1837614 (95.4%) missing values Missing
associatedMedia has 1672693 (86.8%) missing values Missing
associatedSequences has 1921502 (99.7%) missing values Missing
occurrenceRemarks has 1144616 (59.4%) missing values Missing
fieldNumber has 1339917 (69.5%) missing values Missing
eventDate has 684644 (35.5%) missing values Missing
startDayOfYear has 773159 (40.1%) missing values Missing
endDayOfYear has 773330 (40.1%) missing values Missing
year has 684644 (35.5%) missing values Missing
month has 768303 (39.9%) missing values Missing
day has 842091 (43.7%) missing values Missing
verbatimEventDate has 1173351 (60.9%) missing values Missing
habitat has 1857365 (96.4%) missing values Missing
locationID has 984181 (51.1%) missing values Missing
higherGeography has 67836 (3.5%) missing values Missing
continent has 585765 (30.4%) missing values Missing
waterBody has 666725 (34.6%) missing values Missing
islandGroup has 1925854 (> 99.9%) missing values Missing
island has 1925646 (99.9%) missing values Missing
country has 141912 (7.4%) missing values Missing
stateProvince has 943779 (49.0%) missing values Missing
county has 1786637 (92.7%) missing values Missing
locality has 642464 (33.3%) missing values Missing
minimumElevationInMeters has 1919815 (99.6%) missing values Missing
maximumElevationInMeters has 1923105 (99.8%) missing values Missing
verbatimElevation has 1926162 (> 99.9%) missing values Missing
minimumDepthInMeters has 1143921 (59.4%) missing values Missing
maximumDepthInMeters has 1205379 (62.6%) missing values Missing
verbatimDepth has 1900376 (98.6%) missing values Missing
decimalLatitude has 927520 (48.1%) missing values Missing
decimalLongitude has 927523 (48.1%) missing values Missing
geodeticDatum has 1858709 (96.5%) missing values Missing
verbatimLatitude has 1854954 (96.3%) missing values Missing
verbatimLongitude has 1855011 (96.3%) missing values Missing
verbatimCoordinateSystem has 1247024 (64.7%) missing values Missing
georeferenceProtocol has 1265938 (65.7%) missing values Missing
georeferenceRemarks has 1896335 (98.4%) missing values Missing
identificationQualifier has 1908487 (99.1%) missing values Missing
typeStatus has 1838784 (95.4%) missing values Missing
identifiedBy has 1085347 (56.3%) missing values Missing
scientificName has 353809 (18.4%) missing values Missing
class has 76143 (4.0%) missing values Missing
order has 941076 (48.8%) missing values Missing
family has 191873 (10.0%) missing values Missing
genus has 353985 (18.4%) missing values Missing
subgenus has 1813855 (94.1%) missing values Missing
specificEpithet has 354023 (18.4%) missing values Missing
infraspecificEpithet has 1867459 (96.9%) missing values Missing
taxonRank has 1867459 (96.9%) missing values Missing
scientificNameAuthorship has 757161 (39.3%) missing values Missing
gbifID has unique values Unique
occurrenceID has unique values Unique

Reproduction

Analysis started2025-03-26 20:25:35.345418
Analysis finished2025-03-26 20:26:25.510502
Duration50.17 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

gbifID
Text

Unique 

Distinct1926624
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size14.7 MiB
2025-03-26T16:26:26.490806image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters19266240
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1926624 ?
Unique (%)100.0%

Sample

1st row1321728981
2nd row1320179422
3rd row1320179575
4th row1321729723
5th row1320179846
ValueCountFrequency (%)
1321728981 1
 
< 0.1%
2565454742 1
 
< 0.1%
1320179846 1
 
< 0.1%
1321730497 1
 
< 0.1%
1320180949 1
 
< 0.1%
1320181165 1
 
< 0.1%
1456364805 1
 
< 0.1%
1320182209 1
 
< 0.1%
1321732097 1
 
< 0.1%
2571470239 1
 
< 0.1%
Other values (1926614) 1926614
> 99.9%
2025-03-26T16:26:27.522830image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3942125
20.5%
3 2930546
15.2%
2 2444219
12.7%
7 1520086
 
7.9%
8 1484022
 
7.7%
0 1476132
 
7.7%
9 1469215
 
7.6%
5 1371540
 
7.1%
6 1317286
 
6.8%
4 1311069
 
6.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19266240
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 3942125
20.5%
3 2930546
15.2%
2 2444219
12.7%
7 1520086
 
7.9%
8 1484022
 
7.7%
0 1476132
 
7.7%
9 1469215
 
7.6%
5 1371540
 
7.1%
6 1317286
 
6.8%
4 1311069
 
6.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19266240
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 3942125
20.5%
3 2930546
15.2%
2 2444219
12.7%
7 1520086
 
7.9%
8 1484022
 
7.7%
0 1476132
 
7.7%
9 1469215
 
7.6%
5 1371540
 
7.1%
6 1317286
 
6.8%
4 1311069
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19266240
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 3942125
20.5%
3 2930546
15.2%
2 2444219
12.7%
7 1520086
 
7.9%
8 1484022
 
7.7%
0 1476132
 
7.7%
9 1469215
 
7.6%
5 1371540
 
7.1%
6 1317286
 
6.8%
4 1311069
 
6.8%
Distinct113492
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size14.7 MiB
2025-03-26T16:26:27.574834image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters36605856
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62370 ?
Unique (%)3.2%

Sample

1st row2021-10-06 15:29:00
2nd row2024-09-25 16:08:00
3rd row2020-01-06 17:42:00
4th row2018-09-17 12:46:00
5th row2024-09-25 15:32:00
ValueCountFrequency (%)
2024-09-25 692941
 
18.0%
2018-09-17 227606
 
5.9%
2019-11-01 80361
 
2.1%
2021-10-06 56998
 
1.5%
2014-10-08 33487
 
0.9%
2014-10-09 25890
 
0.7%
2017-03-29 25190
 
0.7%
2013-01-10 21870
 
0.6%
2024-08-19 19857
 
0.5%
2014-10-20 17836
 
0.5%
Other values (3940) 2651212
68.8%
2025-03-26T16:26:27.663241image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8972478
24.5%
2 4989098
13.6%
1 4689315
12.8%
- 3853248
10.5%
: 3853248
10.5%
1926624
 
5.3%
4 1757960
 
4.8%
5 1702303
 
4.7%
9 1537171
 
4.2%
3 1150015
 
3.1%
Other values (3) 2174396
 
5.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 36605856
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 8972478
24.5%
2 4989098
13.6%
1 4689315
12.8%
- 3853248
10.5%
: 3853248
10.5%
1926624
 
5.3%
4 1757960
 
4.8%
5 1702303
 
4.7%
9 1537171
 
4.2%
3 1150015
 
3.1%
Other values (3) 2174396
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 36605856
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 8972478
24.5%
2 4989098
13.6%
1 4689315
12.8%
- 3853248
10.5%
: 3853248
10.5%
1926624
 
5.3%
4 1757960
 
4.8%
5 1702303
 
4.7%
9 1537171
 
4.2%
3 1150015
 
3.1%
Other values (3) 2174396
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 36605856
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 8972478
24.5%
2 4989098
13.6%
1 4689315
12.8%
- 3853248
10.5%
: 3853248
10.5%
1926624
 
5.3%
4 1757960
 
4.8%
5 1702303
 
4.7%
9 1537171
 
4.2%
3 1150015
 
3.1%
Other values (3) 2174396
 
5.9%

institutionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size14.7 MiB
2025-03-26T16:26:27.691750image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length29
Mean length29
Min length29

Characters and Unicode

Total characters55872096
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:lsid:biocol.org:col:34871
2nd rowurn:lsid:biocol.org:col:34871
3rd rowurn:lsid:biocol.org:col:34871
4th rowurn:lsid:biocol.org:col:34871
5th rowurn:lsid:biocol.org:col:34871
ValueCountFrequency (%)
urn:lsid:biocol.org:col:34871 1926624
100.0%
2025-03-26T16:26:27.772095image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 7706496
13.8%
: 7706496
13.8%
l 5779872
 
10.3%
i 3853248
 
6.9%
r 3853248
 
6.9%
c 3853248
 
6.9%
g 1926624
 
3.4%
7 1926624
 
3.4%
8 1926624
 
3.4%
4 1926624
 
3.4%
Other values (8) 15412992
27.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 55872096
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 7706496
13.8%
: 7706496
13.8%
l 5779872
 
10.3%
i 3853248
 
6.9%
r 3853248
 
6.9%
c 3853248
 
6.9%
g 1926624
 
3.4%
7 1926624
 
3.4%
8 1926624
 
3.4%
4 1926624
 
3.4%
Other values (8) 15412992
27.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 55872096
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 7706496
13.8%
: 7706496
13.8%
l 5779872
 
10.3%
i 3853248
 
6.9%
r 3853248
 
6.9%
c 3853248
 
6.9%
g 1926624
 
3.4%
7 1926624
 
3.4%
8 1926624
 
3.4%
4 1926624
 
3.4%
Other values (8) 15412992
27.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 55872096
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 7706496
13.8%
: 7706496
13.8%
l 5779872
 
10.3%
i 3853248
 
6.9%
r 3853248
 
6.9%
c 3853248
 
6.9%
g 1926624
 
3.4%
7 1926624
 
3.4%
8 1926624
 
3.4%
4 1926624
 
3.4%
Other values (8) 15412992
27.6%

collectionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size14.7 MiB
2025-03-26T16:26:27.801564image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters86698080
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6
2nd rowurn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6
3rd rowurn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6
4th rowurn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6
5th rowurn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6
ValueCountFrequency (%)
urn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6 1926624
100.0%
2025-03-26T16:26:27.878953image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 9633120
11.1%
1 7706496
 
8.9%
- 7706496
 
8.9%
u 5779872
 
6.7%
8 5779872
 
6.7%
2 5779872
 
6.7%
4 5779872
 
6.7%
c 5779872
 
6.7%
f 5779872
 
6.7%
9 3853248
 
4.4%
Other values (9) 23119488
26.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 86698080
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
d 9633120
11.1%
1 7706496
 
8.9%
- 7706496
 
8.9%
u 5779872
 
6.7%
8 5779872
 
6.7%
2 5779872
 
6.7%
4 5779872
 
6.7%
c 5779872
 
6.7%
f 5779872
 
6.7%
9 3853248
 
4.4%
Other values (9) 23119488
26.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 86698080
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
d 9633120
11.1%
1 7706496
 
8.9%
- 7706496
 
8.9%
u 5779872
 
6.7%
8 5779872
 
6.7%
2 5779872
 
6.7%
4 5779872
 
6.7%
c 5779872
 
6.7%
f 5779872
 
6.7%
9 3853248
 
4.4%
Other values (9) 23119488
26.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 86698080
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
d 9633120
11.1%
1 7706496
 
8.9%
- 7706496
 
8.9%
u 5779872
 
6.7%
8 5779872
 
6.7%
2 5779872
 
6.7%
4 5779872
 
6.7%
c 5779872
 
6.7%
f 5779872
 
6.7%
9 3853248
 
4.4%
Other values (9) 23119488
26.7%

institutionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size14.7 MiB
2025-03-26T16:26:27.907990image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters7706496
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUSNM
2nd rowUSNM
3rd rowUSNM
4th rowUSNM
5th rowUSNM
ValueCountFrequency (%)
usnm 1926624
100.0%
2025-03-26T16:26:27.982768image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 1926624
25.0%
S 1926624
25.0%
N 1926624
25.0%
M 1926624
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7706496
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 1926624
25.0%
S 1926624
25.0%
N 1926624
25.0%
M 1926624
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7706496
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 1926624
25.0%
S 1926624
25.0%
N 1926624
25.0%
M 1926624
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7706496
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 1926624
25.0%
S 1926624
25.0%
N 1926624
25.0%
M 1926624
25.0%

collectionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size14.7 MiB
2025-03-26T16:26:28.009279image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters3853248
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowIZ
2nd rowIZ
3rd rowIZ
4th rowIZ
5th rowIZ
ValueCountFrequency (%)
iz 1926624
100.0%
2025-03-26T16:26:28.082207image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
I 1926624
50.0%
Z 1926624
50.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3853248
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
I 1926624
50.0%
Z 1926624
50.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3853248
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
I 1926624
50.0%
Z 1926624
50.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3853248
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
I 1926624
50.0%
Z 1926624
50.0%

datasetName
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size14.7 MiB
2025-03-26T16:26:28.111717image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters36605856
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNMNH Extant Biology
2nd rowNMNH Extant Biology
3rd rowNMNH Extant Biology
4th rowNMNH Extant Biology
5th rowNMNH Extant Biology
ValueCountFrequency (%)
nmnh 1926624
33.3%
extant 1926624
33.3%
biology 1926624
33.3%
2025-03-26T16:26:28.185907image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 3853248
 
10.5%
3853248
 
10.5%
t 3853248
 
10.5%
o 3853248
 
10.5%
M 1926624
 
5.3%
H 1926624
 
5.3%
E 1926624
 
5.3%
x 1926624
 
5.3%
a 1926624
 
5.3%
n 1926624
 
5.3%
Other values (5) 9633120
26.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 36605856
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 3853248
 
10.5%
3853248
 
10.5%
t 3853248
 
10.5%
o 3853248
 
10.5%
M 1926624
 
5.3%
H 1926624
 
5.3%
E 1926624
 
5.3%
x 1926624
 
5.3%
a 1926624
 
5.3%
n 1926624
 
5.3%
Other values (5) 9633120
26.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 36605856
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 3853248
 
10.5%
3853248
 
10.5%
t 3853248
 
10.5%
o 3853248
 
10.5%
M 1926624
 
5.3%
H 1926624
 
5.3%
E 1926624
 
5.3%
x 1926624
 
5.3%
a 1926624
 
5.3%
n 1926624
 
5.3%
Other values (5) 9633120
26.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 36605856
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 3853248
 
10.5%
3853248
 
10.5%
t 3853248
 
10.5%
o 3853248
 
10.5%
M 1926624
 
5.3%
H 1926624
 
5.3%
E 1926624
 
5.3%
x 1926624
 
5.3%
a 1926624
 
5.3%
n 1926624
 
5.3%
Other values (5) 9633120
26.3%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size14.7 MiB
2025-03-26T16:26:28.213907image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length17
Mean length17.00144034
Min length16

Characters and Unicode

Total characters32755383
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPreservedSpecimen
2nd rowPreservedSpecimen
3rd rowPreservedSpecimen
4th rowPreservedSpecimen
5th rowPreservedSpecimen
ValueCountFrequency (%)
preservedspecimen 1922487
99.8%
machineobservation 3456
 
0.2%
humanobservation 681
 
< 0.1%
2025-03-26T16:26:28.302124image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 9620028
29.4%
r 3849111
11.8%
n 1930761
 
5.9%
i 1930080
 
5.9%
s 1926624
 
5.9%
v 1926624
 
5.9%
c 1925943
 
5.9%
m 1923168
 
5.9%
P 1922487
 
5.9%
p 1922487
 
5.9%
Other values (11) 3878070
11.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 32755383
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 9620028
29.4%
r 3849111
11.8%
n 1930761
 
5.9%
i 1930080
 
5.9%
s 1926624
 
5.9%
v 1926624
 
5.9%
c 1925943
 
5.9%
m 1923168
 
5.9%
P 1922487
 
5.9%
p 1922487
 
5.9%
Other values (11) 3878070
11.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 32755383
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 9620028
29.4%
r 3849111
11.8%
n 1930761
 
5.9%
i 1930080
 
5.9%
s 1926624
 
5.9%
v 1926624
 
5.9%
c 1925943
 
5.9%
m 1923168
 
5.9%
P 1922487
 
5.9%
p 1922487
 
5.9%
Other values (11) 3878070
11.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 32755383
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 9620028
29.4%
r 3849111
11.8%
n 1930761
 
5.9%
i 1930080
 
5.9%
s 1926624
 
5.9%
v 1926624
 
5.9%
c 1925943
 
5.9%
m 1923168
 
5.9%
P 1922487
 
5.9%
p 1922487
 
5.9%
Other values (11) 3878070
11.8%

occurrenceID
Text

Unique 

Distinct1926624
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size14.7 MiB
2025-03-26T16:26:29.182448image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length63
Median length63
Mean length63
Min length63

Characters and Unicode

Total characters121377312
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1926624 ?
Unique (%)100.0%

Sample

1st rowhttp://n2t.net/ark:/65665/3c831e8df-8799-47a1-8dcf-bcb0b77fd3e3
2nd rowhttp://n2t.net/ark:/65665/383ab647e-23a7-4086-b71e-36212ccc0eb2
3rd rowhttp://n2t.net/ark:/65665/383adbf6e-f769-4dc3-8bef-550530af49ee
4th rowhttp://n2t.net/ark:/65665/3c83aad38-c935-46fa-96c3-e450ebb169cf
5th rowhttp://n2t.net/ark:/65665/383b126a6-bf3a-4908-bc33-e4435555fcc5
ValueCountFrequency (%)
http://n2t.net/ark:/65665/3c831e8df-8799-47a1-8dcf-bcb0b77fd3e3 1
 
< 0.1%
http://n2t.net/ark:/65665/3c8609028-15fe-4982-820a-6e4cef3b3db1 1
 
< 0.1%
http://n2t.net/ark:/65665/383b126a6-bf3a-4908-bc33-e4435555fcc5 1
 
< 0.1%
http://n2t.net/ark:/65665/3c843fd56-7874-4858-b938-14fdfcb5544c 1
 
< 0.1%
http://n2t.net/ark:/65665/383bcb698-5477-4feb-9966-d9adae345f09 1
 
< 0.1%
http://n2t.net/ark:/65665/383bfd766-40bc-4ede-82ca-0df3775130f3 1
 
< 0.1%
http://n2t.net/ark:/65665/3c84cf22c-2b9b-49fb-91ed-f85efd9e9fa7 1
 
< 0.1%
http://n2t.net/ark:/65665/383cb8e2a-4f46-4138-82be-3d7989851c9e 1
 
< 0.1%
http://n2t.net/ark:/65665/3c856104b-9825-44b9-8b57-e69b58510bf8 1
 
< 0.1%
http://n2t.net/ark:/65665/3c856ef4e-b135-45c8-8511-c533777f0d7a 1
 
< 0.1%
Other values (1926614) 1926614
> 99.9%
2025-03-26T16:26:30.104262image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 9633120
 
7.9%
6 9395564
 
7.7%
- 7706496
 
6.3%
t 7706496
 
6.3%
5 7462114
 
6.1%
a 6019320
 
5.0%
3 5540059
 
4.6%
e 5538345
 
4.6%
2 5538025
 
4.6%
4 5535249
 
4.6%
Other values (16) 51302524
42.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 121377312
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 9633120
 
7.9%
6 9395564
 
7.7%
- 7706496
 
6.3%
t 7706496
 
6.3%
5 7462114
 
6.1%
a 6019320
 
5.0%
3 5540059
 
4.6%
e 5538345
 
4.6%
2 5538025
 
4.6%
4 5535249
 
4.6%
Other values (16) 51302524
42.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 121377312
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 9633120
 
7.9%
6 9395564
 
7.7%
- 7706496
 
6.3%
t 7706496
 
6.3%
5 7462114
 
6.1%
a 6019320
 
5.0%
3 5540059
 
4.6%
e 5538345
 
4.6%
2 5538025
 
4.6%
4 5535249
 
4.6%
Other values (16) 51302524
42.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 121377312
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 9633120
 
7.9%
6 9395564
 
7.7%
- 7706496
 
6.3%
t 7706496
 
6.3%
5 7462114
 
6.1%
a 6019320
 
5.0%
3 5540059
 
4.6%
e 5538345
 
4.6%
2 5538025
 
4.6%
4 5535249
 
4.6%
Other values (16) 51302524
42.3%
Distinct1355523
Distinct (%)70.4%
Missing5
Missing (%)< 0.1%
Memory size14.7 MiB
2025-03-26T16:26:30.850689image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length16
Median length11
Mean length11.03740698
Min length6

Characters and Unicode

Total characters21264878
Distinct characters63
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1024560 ?
Unique (%)53.2%

Sample

1st rowUSNM 1119015
2nd rowUSNM 55168
3rd rowUSNM 52536
4th rowUSNM E40844
5th rowUSNM 241160
ValueCountFrequency (%)
usnm 1926619
50.0%
31
 
< 0.1%
284908 16
 
< 0.1%
653324 13
 
< 0.1%
5357 11
 
< 0.1%
859036 10
 
< 0.1%
15490 10
 
< 0.1%
224878 10
 
< 0.1%
22869 10
 
< 0.1%
49185 9
 
< 0.1%
Other values (1352278) 1926532
50.0%
2025-03-26T16:26:31.674553image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 1928738
 
9.1%
U 1926726
 
9.1%
1926652
 
9.1%
N 1926619
 
9.1%
S 1926619
 
9.1%
1 1810081
 
8.5%
2 1247725
 
5.9%
3 1148018
 
5.4%
4 1110952
 
5.2%
5 1088471
 
5.1%
Other values (53) 5224277
24.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 21264878
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
M 1928738
 
9.1%
U 1926726
 
9.1%
1926652
 
9.1%
N 1926619
 
9.1%
S 1926619
 
9.1%
1 1810081
 
8.5%
2 1247725
 
5.9%
3 1148018
 
5.4%
4 1110952
 
5.2%
5 1088471
 
5.1%
Other values (53) 5224277
24.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 21264878
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
M 1928738
 
9.1%
U 1926726
 
9.1%
1926652
 
9.1%
N 1926619
 
9.1%
S 1926619
 
9.1%
1 1810081
 
8.5%
2 1247725
 
5.9%
3 1148018
 
5.4%
4 1110952
 
5.2%
5 1088471
 
5.1%
Other values (53) 5224277
24.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 21264878
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
M 1928738
 
9.1%
U 1926726
 
9.1%
1926652
 
9.1%
N 1926619
 
9.1%
S 1926619
 
9.1%
1 1810081
 
8.5%
2 1247725
 
5.9%
3 1148018
 
5.4%
4 1110952
 
5.2%
5 1088471
 
5.1%
Other values (53) 5224277
24.6%

recordNumber
Text

Missing 

Distinct119512
Distinct (%)98.1%
Missing1804854
Missing (%)93.7%
Memory size14.7 MiB
2025-03-26T16:26:31.753941image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length87
Median length14
Mean length13.17353207
Min length1

Characters and Unicode

Total characters1604141
Distinct characters81
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118883 ?
Unique (%)97.6%

Sample

1st rowUSNPC # 001298
2nd rowFPlrv_430
3rd rowH-2284
4th rowUSNPC # 066527
5th rowUSNPC # 009815
ValueCountFrequency (%)
88158
28.7%
usnpc 88077
28.6%
ullz 5210
 
1.7%
rh 1566
 
0.5%
k-rh 1555
 
0.5%
ce16007-event 223
 
0.1%
2208 102
 
< 0.1%
1430 92
 
< 0.1%
1513 80
 
< 0.1%
beauty 75
 
< 0.1%
Other values (119431) 122334
39.8%
2025-03-26T16:26:31.887059image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
185702
 
11.6%
0 161200
 
10.0%
C 97572
 
6.1%
S 95246
 
5.9%
U 94884
 
5.9%
P 94159
 
5.9%
N 93466
 
5.8%
# 88234
 
5.5%
1 83016
 
5.2%
2 65158
 
4.1%
Other values (71) 545504
34.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1604141
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
185702
 
11.6%
0 161200
 
10.0%
C 97572
 
6.1%
S 95246
 
5.9%
U 94884
 
5.9%
P 94159
 
5.9%
N 93466
 
5.8%
# 88234
 
5.5%
1 83016
 
5.2%
2 65158
 
4.1%
Other values (71) 545504
34.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1604141
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
185702
 
11.6%
0 161200
 
10.0%
C 97572
 
6.1%
S 95246
 
5.9%
U 94884
 
5.9%
P 94159
 
5.9%
N 93466
 
5.8%
# 88234
 
5.5%
1 83016
 
5.2%
2 65158
 
4.1%
Other values (71) 545504
34.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1604141
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
185702
 
11.6%
0 161200
 
10.0%
C 97572
 
6.1%
S 95246
 
5.9%
U 94884
 
5.9%
P 94159
 
5.9%
N 93466
 
5.8%
# 88234
 
5.5%
1 83016
 
5.2%
2 65158
 
4.1%
Other values (71) 545504
34.0%

recordedBy
Text

Missing 

Distinct37543
Distinct (%)3.2%
Missing764209
Missing (%)39.7%
Memory size14.7 MiB
2025-03-26T16:26:32.021535image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length186
Median length137
Mean length23.02093572
Min length1

Characters and Unicode

Total characters26759881
Distinct characters89
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16585 ?
Unique (%)1.4%

Sample

1st rowVIMS for BLM/ MMS
2nd rowLgl Ecological Research Associates/ Environmental Science And Engineering For BLM/ MMS
3rd rowUniversity of Southern California
4th rowUnited States Fish Commission
5th rowUnited States Fish Commission
ValueCountFrequency (%)
mms 181035
 
4.2%
blm 181033
 
4.2%
for 178076
 
4.2%
fish 168392
 
3.9%
united 164146
 
3.8%
states 163482
 
3.8%
commission 157103
 
3.7%
149587
 
3.5%
of 101726
 
2.4%
j 101479
 
2.4%
Other values (19082) 2734645
63.9%
2025-03-26T16:26:32.246459image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3118289
 
11.7%
e 2081587
 
7.8%
i 1878249
 
7.0%
n 1615374
 
6.0%
t 1591730
 
5.9%
o 1548674
 
5.8%
s 1529357
 
5.7%
a 1497624
 
5.6%
r 1220600
 
4.6%
M 808432
 
3.0%
Other values (79) 9869965
36.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26759881
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3118289
 
11.7%
e 2081587
 
7.8%
i 1878249
 
7.0%
n 1615374
 
6.0%
t 1591730
 
5.9%
o 1548674
 
5.8%
s 1529357
 
5.7%
a 1497624
 
5.6%
r 1220600
 
4.6%
M 808432
 
3.0%
Other values (79) 9869965
36.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26759881
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3118289
 
11.7%
e 2081587
 
7.8%
i 1878249
 
7.0%
n 1615374
 
6.0%
t 1591730
 
5.9%
o 1548674
 
5.8%
s 1529357
 
5.7%
a 1497624
 
5.6%
r 1220600
 
4.6%
M 808432
 
3.0%
Other values (79) 9869965
36.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26759881
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3118289
 
11.7%
e 2081587
 
7.8%
i 1878249
 
7.0%
n 1615374
 
6.0%
t 1591730
 
5.9%
o 1548674
 
5.8%
s 1529357
 
5.7%
a 1497624
 
5.6%
r 1220600
 
4.6%
M 808432
 
3.0%
Other values (79) 9869965
36.9%
Distinct1067
Distinct (%)0.1%
Missing154
Missing (%)< 0.1%
Memory size14.7 MiB
2025-03-26T16:26:32.292741image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.108391514
Min length1

Characters and Unicode

Total characters2135283
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique413 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row11
3rd row1
4th row26
5th row1
ValueCountFrequency (%)
1 995900
51.7%
2 289604
 
15.0%
3 135791
 
7.0%
4 99117
 
5.1%
5 73934
 
3.8%
6 51752
 
2.7%
10 38954
 
2.0%
7 31383
 
1.6%
8 30170
 
1.6%
9 18505
 
1.0%
Other values (1057) 161360
 
8.4%
2025-03-26T16:26:32.486020image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1131742
53.0%
2 345531
 
16.2%
3 162165
 
7.6%
4 118979
 
5.6%
5 110293
 
5.2%
0 93519
 
4.4%
6 64577
 
3.0%
7 42188
 
2.0%
8 40056
 
1.9%
9 26233
 
1.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2135283
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 1131742
53.0%
2 345531
 
16.2%
3 162165
 
7.6%
4 118979
 
5.6%
5 110293
 
5.2%
0 93519
 
4.4%
6 64577
 
3.0%
7 42188
 
2.0%
8 40056
 
1.9%
9 26233
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2135283
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 1131742
53.0%
2 345531
 
16.2%
3 162165
 
7.6%
4 118979
 
5.6%
5 110293
 
5.2%
0 93519
 
4.4%
6 64577
 
3.0%
7 42188
 
2.0%
8 40056
 
1.9%
9 26233
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2135283
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 1131742
53.0%
2 345531
 
16.2%
3 162165
 
7.6%
4 118979
 
5.6%
5 110293
 
5.2%
0 93519
 
4.4%
6 64577
 
3.0%
7 42188
 
2.0%
8 40056
 
1.9%
9 26233
 
1.2%

sex
Text

Missing 

Distinct299
Distinct (%)0.2%
Missing1744537
Missing (%)90.5%
Memory size14.7 MiB
2025-03-26T16:26:32.515527image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length130
Median length76
Mean length8.258596166
Min length4

Characters and Unicode

Total characters1503783
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique136 ?
Unique (%)0.1%

Sample

1st rowfemale
2nd rowfemale
3rd rowmale; female
4th rowmale
5th rowmale
ValueCountFrequency (%)
female 137602
52.7%
male 121550
46.5%
unknown 1425
 
0.5%
hermaphrodite 267
 
0.1%
224
 
0.1%
intersex 146
 
0.1%
male/female 101
 
< 0.1%
female/male 9
 
< 0.1%
neuter 1
 
< 0.1%
imposex 1
 
< 0.1%
2025-03-26T16:26:32.616794image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 397913
26.5%
a 259639
17.3%
l 259372
17.2%
m 253839
16.9%
f 128884
 
8.6%
; 96895
 
6.4%
79239
 
5.3%
F 8828
 
0.6%
M 5801
 
0.4%
n 4422
 
0.3%
Other values (15) 8951
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1503783
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 397913
26.5%
a 259639
17.3%
l 259372
17.2%
m 253839
16.9%
f 128884
 
8.6%
; 96895
 
6.4%
79239
 
5.3%
F 8828
 
0.6%
M 5801
 
0.4%
n 4422
 
0.3%
Other values (15) 8951
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1503783
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 397913
26.5%
a 259639
17.3%
l 259372
17.2%
m 253839
16.9%
f 128884
 
8.6%
; 96895
 
6.4%
79239
 
5.3%
F 8828
 
0.6%
M 5801
 
0.4%
n 4422
 
0.3%
Other values (15) 8951
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1503783
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 397913
26.5%
a 259639
17.3%
l 259372
17.2%
m 253839
16.9%
f 128884
 
8.6%
; 96895
 
6.4%
79239
 
5.3%
F 8828
 
0.6%
M 5801
 
0.4%
n 4422
 
0.3%
Other values (15) 8951
 
0.6%

lifeStage
Text

Missing 

Distinct853
Distinct (%)1.0%
Missing1837614
Missing (%)95.4%
Memory size14.7 MiB
2025-03-26T16:26:32.647120image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length97
Median length76
Mean length9.342186271
Min length1

Characters and Unicode

Total characters831548
Distinct characters50
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique378 ?
Unique (%)0.4%

Sample

1st rowovigerous
2nd rowI
3rd rowlarva
4th rowjuvenile
5th rowlarvae
ValueCountFrequency (%)
juvenile 43777
33.5%
16549
 
12.7%
ovigerous 15624
 
12.0%
adult 15326
 
11.7%
ii 11921
 
9.1%
i 9499
 
7.3%
larvae 7056
 
5.4%
immature 1741
 
1.3%
larva 1318
 
1.0%
copepodid 667
 
0.5%
Other values (173) 7155
 
5.5%
2025-03-26T16:26:32.752162image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 117697
14.2%
u 78524
9.4%
l 69694
 
8.4%
; 68851
 
8.3%
v 68061
 
8.2%
i 64294
 
7.7%
n 45381
 
5.5%
j 43463
 
5.2%
41623
 
5.0%
a 40332
 
4.9%
Other values (40) 193628
23.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 831548
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 117697
14.2%
u 78524
9.4%
l 69694
 
8.4%
; 68851
 
8.3%
v 68061
 
8.2%
i 64294
 
7.7%
n 45381
 
5.5%
j 43463
 
5.2%
41623
 
5.0%
a 40332
 
4.9%
Other values (40) 193628
23.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 831548
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 117697
14.2%
u 78524
9.4%
l 69694
 
8.4%
; 68851
 
8.3%
v 68061
 
8.2%
i 64294
 
7.7%
n 45381
 
5.5%
j 43463
 
5.2%
41623
 
5.0%
a 40332
 
4.9%
Other values (40) 193628
23.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 831548
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 117697
14.2%
u 78524
9.4%
l 69694
 
8.4%
; 68851
 
8.3%
v 68061
 
8.2%
i 64294
 
7.7%
n 45381
 
5.5%
j 43463
 
5.2%
41623
 
5.0%
a 40332
 
4.9%
Other values (40) 193628
23.3%
Distinct527
Distinct (%)< 0.1%
Missing1858
Missing (%)0.1%
Memory size14.7 MiB
2025-03-26T16:26:32.783163image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length167
Median length157
Mean length10.12225434
Min length3

Characters and Unicode

Total characters19482971
Distinct characters53
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique212 ?
Unique (%)< 0.1%

Sample

1st rowAlcohol (Ethanol)
2nd rowDry
3rd rowAlcohol (Ethanol)
4th rowDry
5th rowDry
ValueCountFrequency (%)
ethanol 907227
30.8%
dry 902453
30.6%
alcohol 897734
30.5%
slide 129659
 
4.4%
19549
 
0.7%
95 16840
 
0.6%
formalin 12587
 
0.4%
biorepository 12374
 
0.4%
isopropyl 10056
 
0.3%
sorting 6036
 
0.2%
Other values (40) 31873
 
1.1%
2025-03-26T16:26:32.888180image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 2866774
14.7%
o 2797522
14.4%
h 1806526
 
9.3%
1021622
 
5.2%
r 954446
 
4.9%
t 939670
 
4.8%
n 936966
 
4.8%
a 925854
 
4.8%
y 924100
 
4.7%
E 913127
 
4.7%
Other values (43) 5396364
27.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19482971
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 2866774
14.7%
o 2797522
14.4%
h 1806526
 
9.3%
1021622
 
5.2%
r 954446
 
4.9%
t 939670
 
4.8%
n 936966
 
4.8%
a 925854
 
4.8%
y 924100
 
4.7%
E 913127
 
4.7%
Other values (43) 5396364
27.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19482971
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 2866774
14.7%
o 2797522
14.4%
h 1806526
 
9.3%
1021622
 
5.2%
r 954446
 
4.9%
t 939670
 
4.8%
n 936966
 
4.8%
a 925854
 
4.8%
y 924100
 
4.7%
E 913127
 
4.7%
Other values (43) 5396364
27.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19482971
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 2866774
14.7%
o 2797522
14.4%
h 1806526
 
9.3%
1021622
 
5.2%
r 954446
 
4.9%
t 939670
 
4.8%
n 936966
 
4.8%
a 925854
 
4.8%
y 924100
 
4.7%
E 913127
 
4.7%
Other values (43) 5396364
27.7%

associatedMedia
Text

Missing 

Distinct242455
Distinct (%)95.5%
Missing1672693
Missing (%)86.8%
Memory size14.7 MiB
2025-03-26T16:26:33.042416image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1629
Median length49
Mean length50.86191524
Min length42

Characters and Unicode

Total characters12915417
Distinct characters31
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique241732 ?
Unique (%)95.2%

Sample

1st rowhttps://collections.nmnh.si.edu/media/?i=12038700
2nd rowhttps://collections.nmnh.si.edu/media/?i=16053651
3rd rowhttps://collections.nmnh.si.edu/media/?i=18190
4th rowhttps://collections.nmnh.si.edu/media/?i=55934
5th rowhttps://collections.nmnh.si.edu/media/?i=10165617
ValueCountFrequency (%)
https://collections.nmnh.si.edu/media/?i=10674432 1623
 
0.5%
https://collections.nmnh.si.edu/media/?i=10689696 1458
 
0.4%
https://collections.nmnh.si.edu/media/?i=10696300 1243
 
0.4%
https://collections.nmnh.si.edu/media/?i=10684813 919
 
0.3%
https://collections.nmnh.si.edu/media/?i=10669453 854
 
0.3%
https://collections.nmnh.si.edu/media/?i=10643018 690
 
0.2%
https://collections.nmnh.si.edu/media/?i=10676407 540
 
0.2%
https://collections.nmnh.si.edu/media/?i=11455178 456
 
0.1%
https://collections.nmnh.si.edu/media/?i=10865403 387
 
0.1%
https://collections.nmnh.si.edu/media/?i=10803950 271
 
0.1%
Other values (311725) 318489
97.4%
2025-03-26T16:26:33.278326image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 1015724
 
7.9%
/ 1015724
 
7.9%
t 761793
 
5.9%
s 761793
 
5.9%
. 761793
 
5.9%
n 761793
 
5.9%
e 761793
 
5.9%
h 507862
 
3.9%
d 507862
 
3.9%
m 507862
 
3.9%
Other values (21) 5551418
43.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12915417
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 1015724
 
7.9%
/ 1015724
 
7.9%
t 761793
 
5.9%
s 761793
 
5.9%
. 761793
 
5.9%
n 761793
 
5.9%
e 761793
 
5.9%
h 507862
 
3.9%
d 507862
 
3.9%
m 507862
 
3.9%
Other values (21) 5551418
43.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12915417
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 1015724
 
7.9%
/ 1015724
 
7.9%
t 761793
 
5.9%
s 761793
 
5.9%
. 761793
 
5.9%
n 761793
 
5.9%
e 761793
 
5.9%
h 507862
 
3.9%
d 507862
 
3.9%
m 507862
 
3.9%
Other values (21) 5551418
43.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12915417
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 1015724
 
7.9%
/ 1015724
 
7.9%
t 761793
 
5.9%
s 761793
 
5.9%
. 761793
 
5.9%
n 761793
 
5.9%
e 761793
 
5.9%
h 507862
 
3.9%
d 507862
 
3.9%
m 507862
 
3.9%
Other values (21) 5551418
43.0%

associatedSequences
Text

Missing 

Distinct5097
Distinct (%)99.5%
Missing1921502
Missing (%)99.7%
Memory size14.7 MiB
2025-03-26T16:26:33.325197image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1349
Median length49
Mean length85.53104256
Min length47

Characters and Unicode

Total characters438090
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5082 ?
Unique (%)99.2%

Sample

1st rowhttps://www.ncbi.nlm.nih.gov/gquery?term=AY426351|https://www.ncbi.nlm.nih.gov/gquery?term=AY379442|https://www.ncbi.nlm.nih.gov/gquery?term=AY426385
2nd rowhttps://www.ncbi.nlm.nih.gov/gquery?term=MH825989
3rd rowhttps://www.ncbi.nlm.nih.gov/gquery?term=MT223244
4th rowhttps://www.ncbi.nlm.nih.gov/gquery?term=MH826372
5th rowhttps://www.ncbi.nlm.nih.gov/gquery?term=KT792656
ValueCountFrequency (%)
https://www.ncbi.nlm.nih.gov/gquery?term=km521547 12
 
0.2%
https://www.ncbi.nlm.nih.gov/gquery?term=kx362316|https://www.ncbi.nlm.nih.gov/gquery?term=kx362269 2
 
< 0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=ef060028|https://www.ncbi.nlm.nih.gov/gquery?term=kx362271 2
 
< 0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=ay643524 2
 
< 0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=srr9613700 2
 
< 0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=fj172481 2
 
< 0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=ku285912 2
 
< 0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=jq307001 2
 
< 0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=kx832080 2
 
< 0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=mk246581|https://www.ncbi.nlm.nih.gov/gquery?term=mk246487 2
 
< 0.1%
Other values (5087) 5092
99.4%
2025-03-26T16:26:33.439875image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 35419
 
8.1%
t 26562
 
6.1%
/ 26562
 
6.1%
w 26562
 
6.1%
n 26562
 
6.1%
h 17708
 
4.0%
r 17708
 
4.0%
i 17708
 
4.0%
e 17708
 
4.0%
m 17708
 
4.0%
Other values (51) 207883
47.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 438090
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 35419
 
8.1%
t 26562
 
6.1%
/ 26562
 
6.1%
w 26562
 
6.1%
n 26562
 
6.1%
h 17708
 
4.0%
r 17708
 
4.0%
i 17708
 
4.0%
e 17708
 
4.0%
m 17708
 
4.0%
Other values (51) 207883
47.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 438090
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 35419
 
8.1%
t 26562
 
6.1%
/ 26562
 
6.1%
w 26562
 
6.1%
n 26562
 
6.1%
h 17708
 
4.0%
r 17708
 
4.0%
i 17708
 
4.0%
e 17708
 
4.0%
m 17708
 
4.0%
Other values (51) 207883
47.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 438090
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 35419
 
8.1%
t 26562
 
6.1%
/ 26562
 
6.1%
w 26562
 
6.1%
n 26562
 
6.1%
h 17708
 
4.0%
r 17708
 
4.0%
i 17708
 
4.0%
e 17708
 
4.0%
m 17708
 
4.0%
Other values (51) 207883
47.5%

occurrenceRemarks
Text

Missing 

Distinct384963
Distinct (%)49.2%
Missing1144616
Missing (%)59.4%
Memory size14.7 MiB
2025-03-26T16:26:33.716191image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2434
Median length1350
Mean length61.33269097
Min length1

Characters and Unicode

Total characters47962655
Distinct characters131
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique322741 ?
Unique (%)41.3%

Sample

1st rowJewett.; Stearns.
2nd rowBartsch
3rd row15 Nov. 1973; Jones, Dawson, del Rosario; Fitzgerald; NMNH-STRI Survey
4th rowU. S. B. Fish
5th rowC.R. Laws
ValueCountFrequency (%)
coll 143211
 
2.1%
of 115180
 
1.7%
and 111365
 
1.7%
a 107285
 
1.6%
by 89615
 
1.3%
87772
 
1.3%
2 65602
 
1.0%
3 63115
 
0.9%
was 62157
 
0.9%
formalin 58894
 
0.9%
Other values (236669) 5767013
86.4%
2025-03-26T16:26:34.050921image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5889201
 
12.3%
e 2962500
 
6.2%
o 2598401
 
5.4%
a 2408453
 
5.0%
i 2005955
 
4.2%
t 1974751
 
4.1%
n 1972339
 
4.1%
r 1874828
 
3.9%
s 1855894
 
3.9%
l 1809811
 
3.8%
Other values (121) 22610522
47.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 47962655
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5889201
 
12.3%
e 2962500
 
6.2%
o 2598401
 
5.4%
a 2408453
 
5.0%
i 2005955
 
4.2%
t 1974751
 
4.1%
n 1972339
 
4.1%
r 1874828
 
3.9%
s 1855894
 
3.9%
l 1809811
 
3.8%
Other values (121) 22610522
47.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 47962655
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5889201
 
12.3%
e 2962500
 
6.2%
o 2598401
 
5.4%
a 2408453
 
5.0%
i 2005955
 
4.2%
t 1974751
 
4.1%
n 1972339
 
4.1%
r 1874828
 
3.9%
s 1855894
 
3.9%
l 1809811
 
3.8%
Other values (121) 22610522
47.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 47962655
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5889201
 
12.3%
e 2962500
 
6.2%
o 2598401
 
5.4%
a 2408453
 
5.0%
i 2005955
 
4.2%
t 1974751
 
4.1%
n 1972339
 
4.1%
r 1874828
 
3.9%
s 1855894
 
3.9%
l 1809811
 
3.8%
Other values (121) 22610522
47.1%

fieldNumber
Text

Missing 

Distinct62655
Distinct (%)10.7%
Missing1339917
Missing (%)69.5%
Memory size14.7 MiB
2025-03-26T16:26:34.207113image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length111
Median length63
Mean length13.61565483
Min length1

Characters and Unicode

Total characters7988400
Distinct characters82
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27492 ?
Unique (%)4.7%

Sample

1st rowMMS-CABP/02B-E4
2nd row4/III-23-TDS
3rd rowUSARP/EL/12/1002/USC
4th rowUSFC/A2059
5th rowUSFC/A5374
ValueCountFrequency (%)
mms-mafla/jar 17294
 
2.6%
bolland/rfb 7605
 
1.1%
humes 5244
 
0.8%
jpem 5029
 
0.8%
4976
 
0.8%
rh 2306
 
0.3%
k-rh 1557
 
0.2%
spm 1164
 
0.2%
mnhn-norfolk 1131
 
0.2%
haul 1040
 
0.2%
Other values (59089) 614516
92.8%
2025-03-26T16:26:34.432322image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 742830
 
9.3%
S 650777
 
8.1%
M 501441
 
6.3%
- 480112
 
6.0%
A 421912
 
5.3%
1 403282
 
5.0%
0 377892
 
4.7%
C 368202
 
4.6%
2 361022
 
4.5%
U 266568
 
3.3%
Other values (72) 3414362
42.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7988400
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 742830
 
9.3%
S 650777
 
8.1%
M 501441
 
6.3%
- 480112
 
6.0%
A 421912
 
5.3%
1 403282
 
5.0%
0 377892
 
4.7%
C 368202
 
4.6%
2 361022
 
4.5%
U 266568
 
3.3%
Other values (72) 3414362
42.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7988400
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 742830
 
9.3%
S 650777
 
8.1%
M 501441
 
6.3%
- 480112
 
6.0%
A 421912
 
5.3%
1 403282
 
5.0%
0 377892
 
4.7%
C 368202
 
4.6%
2 361022
 
4.5%
U 266568
 
3.3%
Other values (72) 3414362
42.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7988400
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 742830
 
9.3%
S 650777
 
8.1%
M 501441
 
6.3%
- 480112
 
6.0%
A 421912
 
5.3%
1 403282
 
5.0%
0 377892
 
4.7%
C 368202
 
4.6%
2 361022
 
4.5%
U 266568
 
3.3%
Other values (72) 3414362
42.7%

eventDate
Text

Missing 

Distinct46452
Distinct (%)3.7%
Missing684644
Missing (%)35.5%
Memory size14.7 MiB
2025-03-26T16:26:34.567191image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length10
Mean length9.847427495
Min length4

Characters and Unicode

Total characters12230308
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7283 ?
Unique (%)0.6%

Sample

1st row1976-03-03
2nd row1984-05-15
3rd row1964-03-15
4th row1883-08-31
5th row1909-03-02
ValueCountFrequency (%)
1915 6243
 
0.5%
1982-07-21 5686
 
0.5%
1981-07-06 5412
 
0.4%
1983-05-13 5157
 
0.4%
1982-11-19 5039
 
0.4%
1982-02-10 4461
 
0.4%
1981-11-09 4298
 
0.3%
1913 4291
 
0.3%
1982-05-10 4269
 
0.3%
1977-01-28/1977-02-13 3795
 
0.3%
Other values (46408) 1193475
96.1%
2025-03-26T16:26:34.766675image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2357254
19.3%
- 2335178
19.1%
0 1811773
14.8%
9 1511115
12.4%
2 833250
 
6.8%
8 785027
 
6.4%
7 719618
 
5.9%
6 567158
 
4.6%
5 438727
 
3.6%
3 433110
 
3.5%
Other values (6) 438098
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12230308
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 2357254
19.3%
- 2335178
19.1%
0 1811773
14.8%
9 1511115
12.4%
2 833250
 
6.8%
8 785027
 
6.4%
7 719618
 
5.9%
6 567158
 
4.6%
5 438727
 
3.6%
3 433110
 
3.5%
Other values (6) 438098
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12230308
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 2357254
19.3%
- 2335178
19.1%
0 1811773
14.8%
9 1511115
12.4%
2 833250
 
6.8%
8 785027
 
6.4%
7 719618
 
5.9%
6 567158
 
4.6%
5 438727
 
3.6%
3 433110
 
3.5%
Other values (6) 438098
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12230308
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 2357254
19.3%
- 2335178
19.1%
0 1811773
14.8%
9 1511115
12.4%
2 833250
 
6.8%
8 785027
 
6.4%
7 719618
 
5.9%
6 567158
 
4.6%
5 438727
 
3.6%
3 433110
 
3.5%
Other values (6) 438098
 
3.6%

startDayOfYear
Text

Missing 

Distinct366
Distinct (%)< 0.1%
Missing773159
Missing (%)40.1%
Memory size14.7 MiB
2025-03-26T16:26:34.915590image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.745111468
Min length1

Characters and Unicode

Total characters3166390
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row63
2nd row136
3rd row75
4th row243
5th row61
ValueCountFrequency (%)
243 12549
 
1.1%
334 10330
 
0.9%
151 9379
 
0.8%
202 9216
 
0.8%
133 9051
 
0.8%
212 8671
 
0.8%
187 8345
 
0.7%
130 7953
 
0.7%
323 7928
 
0.7%
41 7863
 
0.7%
Other values (356) 1062180
92.1%
2025-03-26T16:26:35.114672image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 622646
19.7%
2 591132
18.7%
3 457456
14.4%
4 256956
8.1%
5 233540
 
7.4%
0 218666
 
6.9%
6 207726
 
6.6%
9 203272
 
6.4%
7 193147
 
6.1%
8 181849
 
5.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3166390
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 622646
19.7%
2 591132
18.7%
3 457456
14.4%
4 256956
8.1%
5 233540
 
7.4%
0 218666
 
6.9%
6 207726
 
6.6%
9 203272
 
6.4%
7 193147
 
6.1%
8 181849
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3166390
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 622646
19.7%
2 591132
18.7%
3 457456
14.4%
4 256956
8.1%
5 233540
 
7.4%
0 218666
 
6.9%
6 207726
 
6.6%
9 203272
 
6.4%
7 193147
 
6.1%
8 181849
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3166390
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 622646
19.7%
2 591132
18.7%
3 457456
14.4%
4 256956
8.1%
5 233540
 
7.4%
0 218666
 
6.9%
6 207726
 
6.6%
9 203272
 
6.4%
7 193147
 
6.1%
8 181849
 
5.7%

endDayOfYear
Text

Missing 

Distinct366
Distinct (%)< 0.1%
Missing773330
Missing (%)40.1%
Memory size14.7 MiB
2025-03-26T16:26:35.251206image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.745969371
Min length1

Characters and Unicode

Total characters3166910
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row63
2nd row136
3rd row75
4th row243
5th row61
ValueCountFrequency (%)
243 12441
 
1.1%
334 10165
 
0.9%
151 9377
 
0.8%
202 9191
 
0.8%
133 9039
 
0.8%
212 8814
 
0.8%
187 8348
 
0.7%
41 7969
 
0.7%
323 7926
 
0.7%
130 7870
 
0.7%
Other values (356) 1062154
92.1%
2025-03-26T16:26:35.448652image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 626785
19.8%
2 588517
18.6%
3 458768
14.5%
4 260102
8.2%
5 235638
 
7.4%
0 220467
 
7.0%
6 202498
 
6.4%
9 198709
 
6.3%
7 192188
 
6.1%
8 183238
 
5.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3166910
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 626785
19.8%
2 588517
18.6%
3 458768
14.5%
4 260102
8.2%
5 235638
 
7.4%
0 220467
 
7.0%
6 202498
 
6.4%
9 198709
 
6.3%
7 192188
 
6.1%
8 183238
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3166910
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 626785
19.8%
2 588517
18.6%
3 458768
14.5%
4 260102
8.2%
5 235638
 
7.4%
0 220467
 
7.0%
6 202498
 
6.4%
9 198709
 
6.3%
7 192188
 
6.1%
8 183238
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3166910
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 626785
19.8%
2 588517
18.6%
3 458768
14.5%
4 260102
8.2%
5 235638
 
7.4%
0 220467
 
7.0%
6 202498
 
6.4%
9 198709
 
6.3%
7 192188
 
6.1%
8 183238
 
5.8%

year
Text

Missing 

Distinct208
Distinct (%)< 0.1%
Missing684644
Missing (%)35.5%
Memory size14.7 MiB
2025-03-26T16:26:35.567140image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4967920
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)< 0.1%

Sample

1st row1976
2nd row1984
3rd row1964
4th row1883
5th row1909
ValueCountFrequency (%)
1977 73857
 
5.9%
1981 43902
 
3.5%
1976 42221
 
3.4%
1982 38226
 
3.1%
1984 38210
 
3.1%
1908 35413
 
2.9%
1983 34041
 
2.7%
1985 30501
 
2.5%
1964 28263
 
2.3%
1975 25222
 
2.0%
Other values (198) 852124
68.6%
2025-03-26T16:26:35.728988image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1366365
27.5%
9 1249071
25.1%
8 526282
 
10.6%
7 430044
 
8.7%
6 323975
 
6.5%
0 306387
 
6.2%
2 220380
 
4.4%
5 195047
 
3.9%
4 178264
 
3.6%
3 172105
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4967920
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 1366365
27.5%
9 1249071
25.1%
8 526282
 
10.6%
7 430044
 
8.7%
6 323975
 
6.5%
0 306387
 
6.2%
2 220380
 
4.4%
5 195047
 
3.9%
4 178264
 
3.6%
3 172105
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4967920
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 1366365
27.5%
9 1249071
25.1%
8 526282
 
10.6%
7 430044
 
8.7%
6 323975
 
6.5%
0 306387
 
6.2%
2 220380
 
4.4%
5 195047
 
3.9%
4 178264
 
3.6%
3 172105
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4967920
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 1366365
27.5%
9 1249071
25.1%
8 526282
 
10.6%
7 430044
 
8.7%
6 323975
 
6.5%
0 306387
 
6.2%
2 220380
 
4.4%
5 195047
 
3.9%
4 178264
 
3.6%
3 172105
 
3.5%

month
Text

Missing 

Distinct12
Distinct (%)< 0.1%
Missing768303
Missing (%)39.9%
Memory size14.7 MiB
2025-03-26T16:26:35.772987image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.188968343
Min length1

Characters and Unicode

Total characters1377207
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row5
3rd row3
4th row8
5th row3
ValueCountFrequency (%)
8 133461
11.5%
5 128955
11.1%
7 123561
10.7%
6 108535
9.4%
4 100280
8.7%
11 97508
8.4%
2 97378
8.4%
3 89661
7.7%
9 87634
7.6%
1 69970
6.0%
Other values (2) 121378
10.5%
2025-03-26T16:26:35.859211image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 386364
28.1%
2 150303
 
10.9%
8 133461
 
9.7%
5 128955
 
9.4%
7 123561
 
9.0%
6 108535
 
7.9%
4 100280
 
7.3%
3 89661
 
6.5%
9 87634
 
6.4%
0 68453
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1377207
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 386364
28.1%
2 150303
 
10.9%
8 133461
 
9.7%
5 128955
 
9.4%
7 123561
 
9.0%
6 108535
 
7.9%
4 100280
 
7.3%
3 89661
 
6.5%
9 87634
 
6.4%
0 68453
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1377207
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 386364
28.1%
2 150303
 
10.9%
8 133461
 
9.7%
5 128955
 
9.4%
7 123561
 
9.0%
6 108535
 
7.9%
4 100280
 
7.3%
3 89661
 
6.5%
9 87634
 
6.4%
0 68453
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1377207
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 386364
28.1%
2 150303
 
10.9%
8 133461
 
9.7%
5 128955
 
9.4%
7 123561
 
9.0%
6 108535
 
7.9%
4 100280
 
7.3%
3 89661
 
6.5%
9 87634
 
6.4%
0 68453
 
5.0%

day
Text

Missing 

Distinct31
Distinct (%)< 0.1%
Missing842091
Missing (%)43.7%
Memory size14.7 MiB
2025-03-26T16:26:35.900727image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.705725875
Min length1

Characters and Unicode

Total characters1849916
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row15
3rd row15
4th row31
5th row2
ValueCountFrequency (%)
10 46170
 
4.3%
13 45670
 
4.2%
19 44184
 
4.1%
6 40667
 
3.7%
21 40538
 
3.7%
15 38559
 
3.6%
8 38184
 
3.5%
9 38076
 
3.5%
18 36749
 
3.4%
14 36118
 
3.3%
Other values (21) 679618
62.7%
2025-03-26T16:26:36.075251image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 508722
27.5%
2 433719
23.4%
3 161612
 
8.7%
5 109573
 
5.9%
9 109393
 
5.9%
0 109362
 
5.9%
8 109138
 
5.9%
6 105578
 
5.7%
4 102099
 
5.5%
7 100720
 
5.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1849916
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 508722
27.5%
2 433719
23.4%
3 161612
 
8.7%
5 109573
 
5.9%
9 109393
 
5.9%
0 109362
 
5.9%
8 109138
 
5.9%
6 105578
 
5.7%
4 102099
 
5.5%
7 100720
 
5.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1849916
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 508722
27.5%
2 433719
23.4%
3 161612
 
8.7%
5 109573
 
5.9%
9 109393
 
5.9%
0 109362
 
5.9%
8 109138
 
5.9%
6 105578
 
5.7%
4 102099
 
5.5%
7 100720
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1849916
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 508722
27.5%
2 433719
23.4%
3 161612
 
8.7%
5 109573
 
5.9%
9 109393
 
5.9%
0 109362
 
5.9%
8 109138
 
5.9%
6 105578
 
5.7%
4 102099
 
5.5%
7 100720
 
5.4%

verbatimEventDate
Text

Missing 

Distinct47779
Distinct (%)6.3%
Missing1173351
Missing (%)60.9%
Memory size14.7 MiB
2025-03-26T16:26:36.203274image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length181
Median length11
Mean length11.01797622
Min length1

Characters and Unicode

Total characters8299544
Distinct characters81
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15838 ?
Unique (%)2.1%

Sample

1st row-- --- ----
2nd row15 MAY 1984
3rd row15 MAR 1964
4th row03 MAR 1967
5th row31 AUG 1958
ValueCountFrequency (%)
275938
 
12.6%
may 68636
 
3.1%
aug 65863
 
3.0%
jul 61540
 
2.8%
apr 57943
 
2.6%
feb 53293
 
2.4%
jun 52789
 
2.4%
nov 52218
 
2.4%
mar 46125
 
2.1%
1977 42140
 
1.9%
Other values (8404) 1419149
64.6%
2025-03-26T16:26:36.421029image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1442361
17.4%
1 1077669
13.0%
9 807996
 
9.7%
- 749683
 
9.0%
2 340328
 
4.1%
7 334310
 
4.0%
0 322875
 
3.9%
8 301989
 
3.6%
6 296118
 
3.6%
A 274153
 
3.3%
Other values (71) 2352062
28.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8299544
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1442361
17.4%
1 1077669
13.0%
9 807996
 
9.7%
- 749683
 
9.0%
2 340328
 
4.1%
7 334310
 
4.0%
0 322875
 
3.9%
8 301989
 
3.6%
6 296118
 
3.6%
A 274153
 
3.3%
Other values (71) 2352062
28.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8299544
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1442361
17.4%
1 1077669
13.0%
9 807996
 
9.7%
- 749683
 
9.0%
2 340328
 
4.1%
7 334310
 
4.0%
0 322875
 
3.9%
8 301989
 
3.6%
6 296118
 
3.6%
A 274153
 
3.3%
Other values (71) 2352062
28.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8299544
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1442361
17.4%
1 1077669
13.0%
9 807996
 
9.7%
- 749683
 
9.0%
2 340328
 
4.1%
7 334310
 
4.0%
0 322875
 
3.9%
8 301989
 
3.6%
6 296118
 
3.6%
A 274153
 
3.3%
Other values (71) 2352062
28.3%

habitat
Text

Missing 

Distinct18963
Distinct (%)27.4%
Missing1857365
Missing (%)96.4%
Memory size14.7 MiB
2025-03-26T16:26:36.558672image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length235
Median length159
Mean length19.79869764
Min length1

Characters and Unicode

Total characters1371238
Distinct characters89
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13603 ?
Unique (%)19.6%

Sample

1st rowBeach with fresh water creek running into it
2nd rowFreshwater
3rd rowIn sand
4th rowMangrove
5th rowUnder rocks
ValueCountFrequency (%)
freshwater 9208
 
4.1%
in 6887
 
3.1%
on 6374
 
2.8%
reef 6192
 
2.8%
sand 6092
 
2.7%
coral 5812
 
2.6%
of 4886
 
2.2%
rocks 4639
 
2.1%
sp 4290
 
1.9%
intertidal 4238
 
1.9%
Other values (6965) 165808
73.9%
2025-03-26T16:26:36.765128image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
155167
 
11.3%
e 134105
 
9.8%
a 117971
 
8.6%
r 101206
 
7.4%
n 83058
 
6.1%
s 82896
 
6.0%
o 79806
 
5.8%
t 71853
 
5.2%
i 60755
 
4.4%
l 60225
 
4.4%
Other values (79) 424196
30.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1371238
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
155167
 
11.3%
e 134105
 
9.8%
a 117971
 
8.6%
r 101206
 
7.4%
n 83058
 
6.1%
s 82896
 
6.0%
o 79806
 
5.8%
t 71853
 
5.2%
i 60755
 
4.4%
l 60225
 
4.4%
Other values (79) 424196
30.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1371238
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
155167
 
11.3%
e 134105
 
9.8%
a 117971
 
8.6%
r 101206
 
7.4%
n 83058
 
6.1%
s 82896
 
6.0%
o 79806
 
5.8%
t 71853
 
5.2%
i 60755
 
4.4%
l 60225
 
4.4%
Other values (79) 424196
30.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1371238
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
155167
 
11.3%
e 134105
 
9.8%
a 117971
 
8.6%
r 101206
 
7.4%
n 83058
 
6.1%
s 82896
 
6.0%
o 79806
 
5.8%
t 71853
 
5.2%
i 60755
 
4.4%
l 60225
 
4.4%
Other values (79) 424196
30.9%

locationID
Text

Missing 

Distinct94708
Distinct (%)10.0%
Missing984181
Missing (%)51.1%
Memory size14.7 MiB
2025-03-26T16:26:36.923247image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length146
Median length133
Mean length4.431862723
Min length1

Characters and Unicode

Total characters4176778
Distinct characters88
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52905 ?
Unique (%)5.6%

Sample

1st rowE4
2nd rowNR 12-4 ID 101
3rd row23
4th row1002
5th row2059
ValueCountFrequency (%)
not 12393
 
1.2%
rec 12071
 
1.2%
4 8476
 
0.8%
rhb 7697
 
0.7%
rfb 7623
 
0.7%
1 7565
 
0.7%
2 6224
 
0.6%
3 5489
 
0.5%
gs 5168
 
0.5%
6 5011
 
0.5%
Other values (80229) 962670
92.5%
2025-03-26T16:26:37.148313image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 473548
 
11.3%
2 393337
 
9.4%
0 331212
 
7.9%
5 295532
 
7.1%
3 287180
 
6.9%
4 263624
 
6.3%
- 261734
 
6.3%
6 216195
 
5.2%
7 190512
 
4.6%
8 180399
 
4.3%
Other values (78) 1283505
30.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4176778
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 473548
 
11.3%
2 393337
 
9.4%
0 331212
 
7.9%
5 295532
 
7.1%
3 287180
 
6.9%
4 263624
 
6.3%
- 261734
 
6.3%
6 216195
 
5.2%
7 190512
 
4.6%
8 180399
 
4.3%
Other values (78) 1283505
30.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4176778
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 473548
 
11.3%
2 393337
 
9.4%
0 331212
 
7.9%
5 295532
 
7.1%
3 287180
 
6.9%
4 263624
 
6.3%
- 261734
 
6.3%
6 216195
 
5.2%
7 190512
 
4.6%
8 180399
 
4.3%
Other values (78) 1283505
30.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4176778
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 473548
 
11.3%
2 393337
 
9.4%
0 331212
 
7.9%
5 295532
 
7.1%
3 287180
 
6.9%
4 263624
 
6.3%
- 261734
 
6.3%
6 216195
 
5.2%
7 190512
 
4.6%
8 180399
 
4.3%
Other values (78) 1283505
30.7%

higherGeography
Text

Missing 

Distinct12373
Distinct (%)0.7%
Missing67836
Missing (%)3.5%
Memory size14.7 MiB
2025-03-26T16:26:37.198821image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length126
Median length104
Mean length36.17347433
Min length4

Characters and Unicode

Total characters67238820
Distinct characters78
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3193 ?
Unique (%)0.2%

Sample

1st rowNorth Atlantic Ocean, United States
2nd rowNorth Atlantic Ocean, Gulf of Mexico, United States, Florida
3rd rowNorth Atlantic Ocean, Caribbean Sea, Barbados
4th rowNorth Atlantic Ocean, Gulf of Mexico, United States, Florida
5th rowPhilippines
ValueCountFrequency (%)
ocean 1260066
 
13.4%
north 1098287
 
11.7%
united 886296
 
9.4%
states 871713
 
9.3%
atlantic 718393
 
7.7%
pacific 437058
 
4.7%
mexico 248403
 
2.6%
of 243401
 
2.6%
gulf 228802
 
2.4%
south 203347
 
2.2%
Other values (4652) 3191839
34.0%
2025-03-26T16:26:37.317502image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7528817
 
11.2%
a 6866187
 
10.2%
t 6257560
 
9.3%
i 4780788
 
7.1%
e 4734541
 
7.0%
n 4584981
 
6.8%
c 3760856
 
5.6%
o 2897486
 
4.3%
, 2857645
 
4.2%
r 2272344
 
3.4%
Other values (68) 20697615
30.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 67238820
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
7528817
 
11.2%
a 6866187
 
10.2%
t 6257560
 
9.3%
i 4780788
 
7.1%
e 4734541
 
7.0%
n 4584981
 
6.8%
c 3760856
 
5.6%
o 2897486
 
4.3%
, 2857645
 
4.2%
r 2272344
 
3.4%
Other values (68) 20697615
30.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 67238820
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
7528817
 
11.2%
a 6866187
 
10.2%
t 6257560
 
9.3%
i 4780788
 
7.1%
e 4734541
 
7.0%
n 4584981
 
6.8%
c 3760856
 
5.6%
o 2897486
 
4.3%
, 2857645
 
4.2%
r 2272344
 
3.4%
Other values (68) 20697615
30.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 67238820
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
7528817
 
11.2%
a 6866187
 
10.2%
t 6257560
 
9.3%
i 4780788
 
7.1%
e 4734541
 
7.0%
n 4584981
 
6.8%
c 3760856
 
5.6%
o 2897486
 
4.3%
, 2857645
 
4.2%
r 2272344
 
3.4%
Other values (68) 20697615
30.8%

continent
Text

Missing 

Distinct78
Distinct (%)< 0.1%
Missing585765
Missing (%)30.4%
Memory size14.7 MiB
2025-03-26T16:26:37.348371image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length62
Median length20
Mean length18.74671013
Min length4

Characters and Unicode

Total characters25136695
Distinct characters33
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)< 0.1%

Sample

1st rowNorth Atlantic Ocean
2nd rowNorth Atlantic Ocean
3rd rowNorth Atlantic Ocean
4th rowNorth Atlantic Ocean
5th rowAntarctic Ocean
ValueCountFrequency (%)
ocean 1259591
32.8%
north 1065285
27.7%
atlantic 718331
18.7%
pacific 437017
 
11.4%
south 160803
 
4.2%
america 74610
 
1.9%
indian 50212
 
1.3%
antarctic 43847
 
1.1%
arctic 10184
 
0.3%
asia 8415
 
0.2%
Other values (16) 13317
 
0.3%
2025-03-26T16:26:37.446942image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 3040293
12.1%
t 2764721
11.0%
a 2601186
10.3%
2500753
9.9%
n 2127424
8.5%
i 1785190
 
7.1%
e 1339762
 
5.3%
O 1259591
 
5.0%
o 1231257
 
4.9%
h 1226088
 
4.9%
Other values (23) 5260430
20.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 25136695
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
c 3040293
12.1%
t 2764721
11.0%
a 2601186
10.3%
2500753
9.9%
n 2127424
8.5%
i 1785190
 
7.1%
e 1339762
 
5.3%
O 1259591
 
5.0%
o 1231257
 
4.9%
h 1226088
 
4.9%
Other values (23) 5260430
20.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 25136695
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
c 3040293
12.1%
t 2764721
11.0%
a 2601186
10.3%
2500753
9.9%
n 2127424
8.5%
i 1785190
 
7.1%
e 1339762
 
5.3%
O 1259591
 
5.0%
o 1231257
 
4.9%
h 1226088
 
4.9%
Other values (23) 5260430
20.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 25136695
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
c 3040293
12.1%
t 2764721
11.0%
a 2601186
10.3%
2500753
9.9%
n 2127424
8.5%
i 1785190
 
7.1%
e 1339762
 
5.3%
O 1259591
 
5.0%
o 1231257
 
4.9%
h 1226088
 
4.9%
Other values (23) 5260430
20.9%

waterBody
Text

Missing 

Distinct1655
Distinct (%)0.1%
Missing666725
Missing (%)34.6%
Memory size14.7 MiB
2025-03-26T16:26:37.483948image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length76
Median length75
Mean length24.49179815
Min length7

Characters and Unicode

Total characters30857192
Distinct characters63
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique510 ?
Unique (%)< 0.1%

Sample

1st rowNorth Atlantic Ocean
2nd rowNorth Atlantic Ocean, Gulf of Mexico
3rd rowNorth Atlantic Ocean, Caribbean Sea
4th rowNorth Atlantic Ocean, Gulf of Mexico
5th rowAntarctic Ocean
ValueCountFrequency (%)
ocean 1259591
26.1%
north 998680
20.7%
atlantic 718331
14.9%
pacific 437017
 
9.1%
of 231344
 
4.8%
gulf 228669
 
4.7%
sea 193916
 
4.0%
mexico 187781
 
3.9%
south 160389
 
3.3%
caribbean 89366
 
1.9%
Other values (1319) 318057
 
6.6%
2025-03-26T16:26:37.593272image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3563242
11.5%
c 3176297
10.3%
a 3113911
 
10.1%
t 2739265
 
8.9%
n 2331911
 
7.6%
i 2083003
 
6.8%
e 1823921
 
5.9%
o 1648534
 
5.3%
O 1261284
 
4.1%
r 1218293
 
3.9%
Other values (53) 7897531
25.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 30857192
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3563242
11.5%
c 3176297
10.3%
a 3113911
 
10.1%
t 2739265
 
8.9%
n 2331911
 
7.6%
i 2083003
 
6.8%
e 1823921
 
5.9%
o 1648534
 
5.3%
O 1261284
 
4.1%
r 1218293
 
3.9%
Other values (53) 7897531
25.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 30857192
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3563242
11.5%
c 3176297
10.3%
a 3113911
 
10.1%
t 2739265
 
8.9%
n 2331911
 
7.6%
i 2083003
 
6.8%
e 1823921
 
5.9%
o 1648534
 
5.3%
O 1261284
 
4.1%
r 1218293
 
3.9%
Other values (53) 7897531
25.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 30857192
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3563242
11.5%
c 3176297
10.3%
a 3113911
 
10.1%
t 2739265
 
8.9%
n 2331911
 
7.6%
i 2083003
 
6.8%
e 1823921
 
5.9%
o 1648534
 
5.3%
O 1261284
 
4.1%
r 1218293
 
3.9%
Other values (53) 7897531
25.6%

islandGroup
Text

Missing 

Distinct20
Distinct (%)2.6%
Missing1925854
Missing (%)> 99.9%
Memory size14.7 MiB
2025-03-26T16:26:37.625609image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length15
Mean length14.52857143
Min length5

Characters and Unicode

Total characters11187
Distinct characters35
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)0.8%

Sample

1st rowSociety Islands
2nd rowSociety Islands
3rd rowSociety Islands
4th rowSociety Islands
5th rowSociety Islands
ValueCountFrequency (%)
islands 707
47.0%
society 679
45.2%
exuma 20
 
1.3%
south 12
 
0.8%
sandwich 12
 
0.8%
florida 10
 
0.7%
keys 10
 
0.7%
pacific 10
 
0.7%
carolina 8
 
0.5%
aleutian 7
 
0.5%
Other values (14) 28
 
1.9%
2025-03-26T16:26:37.715176image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 1446
12.9%
a 803
 
7.2%
l 751
 
6.7%
n 748
 
6.7%
i 743
 
6.6%
d 738
 
6.6%
733
 
6.6%
o 722
 
6.5%
c 713
 
6.4%
e 711
 
6.4%
Other values (25) 3079
27.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11187
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 1446
12.9%
a 803
 
7.2%
l 751
 
6.7%
n 748
 
6.7%
i 743
 
6.6%
d 738
 
6.6%
733
 
6.6%
o 722
 
6.5%
c 713
 
6.4%
e 711
 
6.4%
Other values (25) 3079
27.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11187
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 1446
12.9%
a 803
 
7.2%
l 751
 
6.7%
n 748
 
6.7%
i 743
 
6.6%
d 738
 
6.6%
733
 
6.6%
o 722
 
6.5%
c 713
 
6.4%
e 711
 
6.4%
Other values (25) 3079
27.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11187
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 1446
12.9%
a 803
 
7.2%
l 751
 
6.7%
n 748
 
6.7%
i 743
 
6.6%
d 738
 
6.6%
733
 
6.6%
o 722
 
6.5%
c 713
 
6.4%
e 711
 
6.4%
Other values (25) 3079
27.5%

island
Text

Missing 

Distinct58
Distinct (%)5.9%
Missing1925646
Missing (%)99.9%
Memory size14.7 MiB
2025-03-26T16:26:37.744001image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length25
Median length6
Mean length6.676891616
Min length4

Characters and Unicode

Total characters6530
Distinct characters49
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)3.4%

Sample

1st rowMoorea
2nd rowMoorea
3rd rowShikoku
4th rowOahu
5th rowMoorea
ValueCountFrequency (%)
moorea 674
60.4%
oahu 147
 
13.2%
island 91
 
8.2%
great 20
 
1.8%
exuma 20
 
1.8%
nunivak 13
 
1.2%
eniwetok 13
 
1.2%
bonaire 11
 
1.0%
key 10
 
0.9%
west 10
 
0.9%
Other values (58) 106
 
9.5%
2025-03-26T16:26:37.832965image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 1430
21.9%
a 1060
16.2%
e 771
11.8%
r 737
11.3%
M 683
10.5%
u 225
 
3.4%
n 186
 
2.8%
h 170
 
2.6%
O 154
 
2.4%
137
 
2.1%
Other values (39) 977
15.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6530
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 1430
21.9%
a 1060
16.2%
e 771
11.8%
r 737
11.3%
M 683
10.5%
u 225
 
3.4%
n 186
 
2.8%
h 170
 
2.6%
O 154
 
2.4%
137
 
2.1%
Other values (39) 977
15.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6530
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 1430
21.9%
a 1060
16.2%
e 771
11.8%
r 737
11.3%
M 683
10.5%
u 225
 
3.4%
n 186
 
2.8%
h 170
 
2.6%
O 154
 
2.4%
137
 
2.1%
Other values (39) 977
15.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6530
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 1430
21.9%
a 1060
16.2%
e 771
11.8%
r 737
11.3%
M 683
10.5%
u 225
 
3.4%
n 186
 
2.8%
h 170
 
2.6%
O 154
 
2.4%
137
 
2.1%
Other values (39) 977
15.0%

country
Text

Missing 

Distinct353
Distinct (%)< 0.1%
Missing141912
Missing (%)7.4%
Memory size14.7 MiB
2025-03-26T16:26:37.959340image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length44
Median length42
Mean length10.90555395
Min length4

Characters and Unicode

Total characters19463273
Distinct characters60
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)< 0.1%

Sample

1st rowUnited States
2nd rowUnited States
3rd rowBarbados
4th rowUnited States
5th rowPhilippines
ValueCountFrequency (%)
united 886292
30.7%
states 871710
30.2%
philippines 93802
 
3.2%
mexico 58648
 
2.0%
islands 48881
 
1.7%
panama 46146
 
1.6%
antarctica 40214
 
1.4%
japan 38469
 
1.3%
cuba 30051
 
1.0%
new 28729
 
1.0%
Other values (297) 748097
25.9%
2025-03-26T16:26:38.164694image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 2859990
14.7%
e 2265482
11.6%
a 2127187
10.9%
i 1744253
9.0%
n 1526102
7.8%
s 1262794
 
6.5%
d 1114140
 
5.7%
1106327
 
5.7%
S 918445
 
4.7%
U 889638
 
4.6%
Other values (50) 3648915
18.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19463273
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 2859990
14.7%
e 2265482
11.6%
a 2127187
10.9%
i 1744253
9.0%
n 1526102
7.8%
s 1262794
 
6.5%
d 1114140
 
5.7%
1106327
 
5.7%
S 918445
 
4.7%
U 889638
 
4.6%
Other values (50) 3648915
18.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19463273
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 2859990
14.7%
e 2265482
11.6%
a 2127187
10.9%
i 1744253
9.0%
n 1526102
7.8%
s 1262794
 
6.5%
d 1114140
 
5.7%
1106327
 
5.7%
S 918445
 
4.7%
U 889638
 
4.6%
Other values (50) 3648915
18.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19463273
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 2859990
14.7%
e 2265482
11.6%
a 2127187
10.9%
i 1744253
9.0%
n 1526102
7.8%
s 1262794
 
6.5%
d 1114140
 
5.7%
1106327
 
5.7%
S 918445
 
4.7%
U 889638
 
4.6%
Other values (50) 3648915
18.7%

stateProvince
Text

Missing 

Distinct1326
Distinct (%)0.1%
Missing943779
Missing (%)49.0%
Memory size14.7 MiB
2025-03-26T16:26:38.299177image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length51
Median length39
Mean length9.182756182
Min length3

Characters and Unicode

Total characters9025226
Distinct characters70
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique281 ?
Unique (%)< 0.1%

Sample

1st rowFlorida
2nd rowFlorida
3rd rowMassachusetts
4th rowQuezon
5th rowNewfoundland
ValueCountFrequency (%)
florida 158001
 
13.1%
massachusetts 103397
 
8.6%
california 57093
 
4.7%
carolina 53938
 
4.5%
texas 43598
 
3.6%
alaska 41864
 
3.5%
north 31998
 
2.7%
louisiana 28649
 
2.4%
hawaii 26401
 
2.2%
south 26219
 
2.2%
Other values (1250) 635105
52.7%
2025-03-26T16:26:38.496976image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1428135
15.8%
i 809103
 
9.0%
s 773354
 
8.6%
o 650969
 
7.2%
r 519515
 
5.8%
l 506730
 
5.6%
n 498728
 
5.5%
e 457690
 
5.1%
t 400689
 
4.4%
u 277375
 
3.1%
Other values (60) 2702938
29.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9025226
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1428135
15.8%
i 809103
 
9.0%
s 773354
 
8.6%
o 650969
 
7.2%
r 519515
 
5.8%
l 506730
 
5.6%
n 498728
 
5.5%
e 457690
 
5.1%
t 400689
 
4.4%
u 277375
 
3.1%
Other values (60) 2702938
29.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9025226
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1428135
15.8%
i 809103
 
9.0%
s 773354
 
8.6%
o 650969
 
7.2%
r 519515
 
5.8%
l 506730
 
5.6%
n 498728
 
5.5%
e 457690
 
5.1%
t 400689
 
4.4%
u 277375
 
3.1%
Other values (60) 2702938
29.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9025226
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1428135
15.8%
i 809103
 
9.0%
s 773354
 
8.6%
o 650969
 
7.2%
r 519515
 
5.8%
l 506730
 
5.6%
n 498728
 
5.5%
e 457690
 
5.1%
t 400689
 
4.4%
u 277375
 
3.1%
Other values (60) 2702938
29.9%

county
Text

Missing 

Distinct2594
Distinct (%)1.9%
Missing1786637
Missing (%)92.7%
Memory size14.7 MiB
2025-03-26T16:26:38.636931image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length46
Median length43
Mean length14.35977626
Min length3

Characters and Unicode

Total characters2010182
Distinct characters65
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique558 ?
Unique (%)0.4%

Sample

1st rowCumberland County
2nd rowAllamakee County
3rd rowSt. Lucie County
4th rowDelaware County
5th rowKimble County
ValueCountFrequency (%)
county 135437
45.4%
st 3893
 
1.3%
parish 3203
 
1.1%
monroe 3117
 
1.0%
lucie 2649
 
0.9%
montgomery 2553
 
0.9%
san 2117
 
0.7%
prince 1875
 
0.6%
george's 1763
 
0.6%
jackson 1749
 
0.6%
Other values (2256) 139889
46.9%
2025-03-26T16:26:38.941035image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 223790
11.1%
o 216867
10.8%
t 181067
 
9.0%
u 160940
 
8.0%
158258
 
7.9%
C 152431
 
7.6%
y 151836
 
7.6%
e 105744
 
5.3%
a 103281
 
5.1%
r 74026
 
3.7%
Other values (55) 481942
24.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2010182
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 223790
11.1%
o 216867
10.8%
t 181067
 
9.0%
u 160940
 
8.0%
158258
 
7.9%
C 152431
 
7.6%
y 151836
 
7.6%
e 105744
 
5.3%
a 103281
 
5.1%
r 74026
 
3.7%
Other values (55) 481942
24.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2010182
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 223790
11.1%
o 216867
10.8%
t 181067
 
9.0%
u 160940
 
8.0%
158258
 
7.9%
C 152431
 
7.6%
y 151836
 
7.6%
e 105744
 
5.3%
a 103281
 
5.1%
r 74026
 
3.7%
Other values (55) 481942
24.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2010182
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 223790
11.1%
o 216867
10.8%
t 181067
 
9.0%
u 160940
 
8.0%
158258
 
7.9%
C 152431
 
7.6%
y 151836
 
7.6%
e 105744
 
5.3%
a 103281
 
5.1%
r 74026
 
3.7%
Other values (55) 481942
24.0%

locality
Text

Missing 

Distinct204774
Distinct (%)15.9%
Missing642464
Missing (%)33.3%
Memory size14.7 MiB
2025-03-26T16:26:39.103530image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length588
Median length368
Mean length28.9673047
Min length1

Characters and Unicode

Total characters37198654
Distinct characters137
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique126344 ?
Unique (%)9.8%

Sample

1st rowoff Delaware
2nd rowW Coast
3rd rowCape Sable, West Of
4th rowAntarctic Peninsula
5th rowGeorges Bank
ValueCountFrequency (%)
island 342386
 
5.6%
of 336456
 
5.5%
off 252698
 
4.1%
bay 137548
 
2.2%
islands 98153
 
1.6%
bank 84608
 
1.4%
south 74634
 
1.2%
georges 66671
 
1.1%
florida 63429
 
1.0%
river 63375
 
1.0%
Other values (76631) 4633281
75.3%
2025-03-26T16:26:39.343124image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4869079
 
13.1%
a 3497112
 
9.4%
e 2450344
 
6.6%
o 2296052
 
6.2%
n 2154259
 
5.8%
r 1673991
 
4.5%
s 1628449
 
4.4%
i 1596852
 
4.3%
l 1583745
 
4.3%
t 1475103
 
4.0%
Other values (127) 13973668
37.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 37198654
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4869079
 
13.1%
a 3497112
 
9.4%
e 2450344
 
6.6%
o 2296052
 
6.2%
n 2154259
 
5.8%
r 1673991
 
4.5%
s 1628449
 
4.4%
i 1596852
 
4.3%
l 1583745
 
4.3%
t 1475103
 
4.0%
Other values (127) 13973668
37.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 37198654
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4869079
 
13.1%
a 3497112
 
9.4%
e 2450344
 
6.6%
o 2296052
 
6.2%
n 2154259
 
5.8%
r 1673991
 
4.5%
s 1628449
 
4.4%
i 1596852
 
4.3%
l 1583745
 
4.3%
t 1475103
 
4.0%
Other values (127) 13973668
37.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 37198654
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4869079
 
13.1%
a 3497112
 
9.4%
e 2450344
 
6.6%
o 2296052
 
6.2%
n 2154259
 
5.8%
r 1673991
 
4.5%
s 1628449
 
4.4%
i 1596852
 
4.3%
l 1583745
 
4.3%
t 1475103
 
4.0%
Other values (127) 13973668
37.6%
Distinct1039
Distinct (%)15.3%
Missing1919815
Missing (%)99.6%
Memory size14.7 MiB
2025-03-26T16:26:39.479928image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.35923043
Min length3

Characters and Unicode

Total characters36491
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique395 ?
Unique (%)5.8%

Sample

1st row783.0
2nd row15.0
3rd row135.0
4th row4070.0
5th row870.0
ValueCountFrequency (%)
1981.0 618
 
9.1%
135.0 196
 
2.9%
350.0 165
 
2.4%
348.0 125
 
1.8%
164.0 123
 
1.8%
149.0 117
 
1.7%
309.0 116
 
1.7%
388.0 86
 
1.3%
988.0 82
 
1.2%
1100.0 72
 
1.1%
Other values (1029) 5109
75.0%
2025-03-26T16:26:39.672682image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9237
25.3%
. 6809
18.7%
1 4983
13.7%
2 2404
 
6.6%
8 2373
 
6.5%
3 2287
 
6.3%
9 2002
 
5.5%
5 1844
 
5.1%
4 1684
 
4.6%
7 1455
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 36491
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 9237
25.3%
. 6809
18.7%
1 4983
13.7%
2 2404
 
6.6%
8 2373
 
6.5%
3 2287
 
6.3%
9 2002
 
5.5%
5 1844
 
5.1%
4 1684
 
4.6%
7 1455
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 36491
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 9237
25.3%
. 6809
18.7%
1 4983
13.7%
2 2404
 
6.6%
8 2373
 
6.5%
3 2287
 
6.3%
9 2002
 
5.5%
5 1844
 
5.1%
4 1684
 
4.6%
7 1455
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 36491
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 9237
25.3%
. 6809
18.7%
1 4983
13.7%
2 2404
 
6.6%
8 2373
 
6.5%
3 2287
 
6.3%
9 2002
 
5.5%
5 1844
 
5.1%
4 1684
 
4.6%
7 1455
 
4.0%
Distinct725
Distinct (%)20.6%
Missing1923105
Missing (%)99.8%
Memory size14.7 MiB
2025-03-26T16:26:39.809012image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.354930378
Min length3

Characters and Unicode

Total characters18844
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique261 ?
Unique (%)7.4%

Sample

1st row783.0
2nd row15.0
3rd row185.0
4th row870.0
5th row853.0
ValueCountFrequency (%)
185.0 198
 
5.6%
914.0 57
 
1.6%
1524.0 48
 
1.4%
1100.0 45
 
1.3%
610.0 40
 
1.1%
1219.0 37
 
1.1%
1829.0 34
 
1.0%
1372.0 33
 
0.9%
2.0 33
 
0.9%
65.0 32
 
0.9%
Other values (715) 2962
84.2%
2025-03-26T16:26:40.008765image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5073
26.9%
. 3519
18.7%
1 2463
13.1%
2 1468
 
7.8%
5 1253
 
6.6%
3 983
 
5.2%
8 942
 
5.0%
6 851
 
4.5%
4 837
 
4.4%
7 737
 
3.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 18844
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 5073
26.9%
. 3519
18.7%
1 2463
13.1%
2 1468
 
7.8%
5 1253
 
6.6%
3 983
 
5.2%
8 942
 
5.0%
6 851
 
4.5%
4 837
 
4.4%
7 737
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 18844
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 5073
26.9%
. 3519
18.7%
1 2463
13.1%
2 1468
 
7.8%
5 1253
 
6.6%
3 983
 
5.2%
8 942
 
5.0%
6 851
 
4.5%
4 837
 
4.4%
7 737
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 18844
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 5073
26.9%
. 3519
18.7%
1 2463
13.1%
2 1468
 
7.8%
5 1253
 
6.6%
3 983
 
5.2%
8 942
 
5.0%
6 851
 
4.5%
4 837
 
4.4%
7 737
 
3.9%

verbatimElevation
Text

Missing 

Distinct126
Distinct (%)27.3%
Missing1926162
Missing (%)> 99.9%
Memory size14.7 MiB
2025-03-26T16:26:40.081170image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length44
Median length4
Mean length10.17099567
Min length4

Characters and Unicode

Total characters4699
Distinct characters51
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)14.1%

Sample

1st row7000
2nd row4070 m.a.s.l.
3rd row4200-4400
4th row2009 +/- 20.1 feet
5th row3000
ValueCountFrequency (%)
collected 53
 
5.6%
on 53
 
5.6%
and 51
 
5.4%
flat 50
 
5.3%
lagoon 50
 
5.3%
slope 50
 
5.3%
m 27
 
2.8%
3800 23
 
2.4%
2550 21
 
2.2%
above 19
 
2.0%
Other values (148) 554
58.3%
2025-03-26T16:26:40.210792image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 660
14.0%
489
 
10.4%
l 346
 
7.4%
e 330
 
7.0%
o 320
 
6.8%
a 237
 
5.0%
3 219
 
4.7%
5 218
 
4.6%
t 202
 
4.3%
n 193
 
4.1%
Other values (41) 1485
31.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4699
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 660
14.0%
489
 
10.4%
l 346
 
7.4%
e 330
 
7.0%
o 320
 
6.8%
a 237
 
5.0%
3 219
 
4.7%
5 218
 
4.6%
t 202
 
4.3%
n 193
 
4.1%
Other values (41) 1485
31.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4699
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 660
14.0%
489
 
10.4%
l 346
 
7.4%
e 330
 
7.0%
o 320
 
6.8%
a 237
 
5.0%
3 219
 
4.7%
5 218
 
4.6%
t 202
 
4.3%
n 193
 
4.1%
Other values (41) 1485
31.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4699
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 660
14.0%
489
 
10.4%
l 346
 
7.4%
e 330
 
7.0%
o 320
 
6.8%
a 237
 
5.0%
3 219
 
4.7%
5 218
 
4.6%
t 202
 
4.3%
n 193
 
4.1%
Other values (41) 1485
31.6%

minimumDepthInMeters
Text

Missing 

Distinct6902
Distinct (%)0.9%
Missing1143921
Missing (%)59.4%
Memory size14.7 MiB
2025-03-26T16:26:40.338253image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.378064221
Min length3

Characters and Unicode

Total characters3426724
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2028 ?
Unique (%)0.3%

Sample

1st row77.0
2nd row50.0
3rd row74.0
4th row265.0
5th row75.0
ValueCountFrequency (%)
0.0 45238
 
5.8%
1.0 16091
 
2.1%
18.0 10812
 
1.4%
2.0 9891
 
1.3%
15.0 9294
 
1.2%
84.0 9273
 
1.2%
82.0 8941
 
1.1%
3.0 8673
 
1.1%
27.0 8650
 
1.1%
55.0 8481
 
1.1%
Other values (6887) 647359
82.7%
2025-03-26T16:26:40.524404image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 982075
28.7%
. 782703
22.8%
1 321246
 
9.4%
2 239322
 
7.0%
5 194481
 
5.7%
3 185532
 
5.4%
4 175142
 
5.1%
8 152616
 
4.5%
6 145166
 
4.2%
7 129355
 
3.8%
Other values (2) 119086
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3426724
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 982075
28.7%
. 782703
22.8%
1 321246
 
9.4%
2 239322
 
7.0%
5 194481
 
5.7%
3 185532
 
5.4%
4 175142
 
5.1%
8 152616
 
4.5%
6 145166
 
4.2%
7 129355
 
3.8%
Other values (2) 119086
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3426724
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 982075
28.7%
. 782703
22.8%
1 321246
 
9.4%
2 239322
 
7.0%
5 194481
 
5.7%
3 185532
 
5.4%
4 175142
 
5.1%
8 152616
 
4.5%
6 145166
 
4.2%
7 129355
 
3.8%
Other values (2) 119086
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3426724
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 982075
28.7%
. 782703
22.8%
1 321246
 
9.4%
2 239322
 
7.0%
5 194481
 
5.7%
3 185532
 
5.4%
4 175142
 
5.1%
8 152616
 
4.5%
6 145166
 
4.2%
7 129355
 
3.8%
Other values (2) 119086
 
3.5%

maximumDepthInMeters
Text

Missing 

Distinct6652
Distinct (%)0.9%
Missing1205379
Missing (%)62.6%
Memory size14.7 MiB
2025-03-26T16:26:40.662208image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.453171946
Min length3

Characters and Unicode

Total characters3211828
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1919 ?
Unique (%)0.3%

Sample

1st row77.0
2nd row400.0
3rd row74.0
4th row265.0
5th row75.0
ValueCountFrequency (%)
1.0 27354
 
3.8%
2.0 10564
 
1.5%
18.0 9726
 
1.3%
84.0 9134
 
1.3%
3.0 8394
 
1.2%
55.0 7486
 
1.0%
27.0 7199
 
1.0%
37.0 6994
 
1.0%
5.0 6771
 
0.9%
0.0 6752
 
0.9%
Other values (6637) 620871
86.1%
2025-03-26T16:26:40.858787image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 885648
27.6%
. 721245
22.5%
1 324008
 
10.1%
2 234862
 
7.3%
5 184742
 
5.8%
3 176946
 
5.5%
4 166769
 
5.2%
8 143387
 
4.5%
6 138579
 
4.3%
7 123074
 
3.8%
Other values (2) 112568
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3211828
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 885648
27.6%
. 721245
22.5%
1 324008
 
10.1%
2 234862
 
7.3%
5 184742
 
5.8%
3 176946
 
5.5%
4 166769
 
5.2%
8 143387
 
4.5%
6 138579
 
4.3%
7 123074
 
3.8%
Other values (2) 112568
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3211828
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 885648
27.6%
. 721245
22.5%
1 324008
 
10.1%
2 234862
 
7.3%
5 184742
 
5.8%
3 176946
 
5.5%
4 166769
 
5.2%
8 143387
 
4.5%
6 138579
 
4.3%
7 123074
 
3.8%
Other values (2) 112568
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3211828
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 885648
27.6%
. 721245
22.5%
1 324008
 
10.1%
2 234862
 
7.3%
5 184742
 
5.8%
3 176946
 
5.5%
4 166769
 
5.2%
8 143387
 
4.5%
6 138579
 
4.3%
7 123074
 
3.8%
Other values (2) 112568
 
3.5%

verbatimDepth
Text

Missing 

Distinct1530
Distinct (%)5.8%
Missing1900376
Missing (%)98.6%
Memory size14.7 MiB
2025-03-26T16:26:40.995101image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length99
Median length91
Mean length13.43748095
Min length1

Characters and Unicode

Total characters352707
Distinct characters79
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique721 ?
Unique (%)2.7%

Sample

1st rowSurface
2nd rowmax depth 1772 ft
3rd rowsurface
4th rowIntertidal
5th rowIntertidal
ValueCountFrequency (%)
intertidal 11933
23.4%
surface 4086
 
8.0%
recorded 2871
 
5.6%
depths 2850
 
5.6%
multiple 2846
 
5.6%
shore 1165
 
2.3%
0-300 1120
 
2.2%
0 1069
 
2.1%
depth 1025
 
2.0%
low 964
 
1.9%
Other values (1043) 21008
41.2%
2025-03-26T16:26:41.204468image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 36693
 
10.4%
e 35149
 
10.0%
r 25394
 
7.2%
24689
 
7.0%
d 24180
 
6.9%
l 20653
 
5.9%
a 20485
 
5.8%
i 19394
 
5.5%
0 16029
 
4.5%
n 14730
 
4.2%
Other values (69) 115311
32.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 352707
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 36693
 
10.4%
e 35149
 
10.0%
r 25394
 
7.2%
24689
 
7.0%
d 24180
 
6.9%
l 20653
 
5.9%
a 20485
 
5.8%
i 19394
 
5.5%
0 16029
 
4.5%
n 14730
 
4.2%
Other values (69) 115311
32.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 352707
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 36693
 
10.4%
e 35149
 
10.0%
r 25394
 
7.2%
24689
 
7.0%
d 24180
 
6.9%
l 20653
 
5.9%
a 20485
 
5.8%
i 19394
 
5.5%
0 16029
 
4.5%
n 14730
 
4.2%
Other values (69) 115311
32.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 352707
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 36693
 
10.4%
e 35149
 
10.0%
r 25394
 
7.2%
24689
 
7.0%
d 24180
 
6.9%
l 20653
 
5.9%
a 20485
 
5.8%
i 19394
 
5.5%
0 16029
 
4.5%
n 14730
 
4.2%
Other values (69) 115311
32.7%

decimalLatitude
Text

Missing 

Distinct70082
Distinct (%)7.0%
Missing927520
Missing (%)48.1%
Memory size14.7 MiB
2025-03-26T16:26:41.349965image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length7
Mean length6.235827301
Min length3

Characters and Unicode

Total characters6230240
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26220 ?
Unique (%)2.6%

Sample

1st row38.7117
2nd row25.2819
3rd row-62.667
4th row42.0833
5th row13.7792
ValueCountFrequency (%)
25.58 10491
 
1.1%
40.6583 8822
 
0.9%
26.17 7320
 
0.7%
26.5 5192
 
0.5%
26.97 3956
 
0.4%
25.7883 3458
 
0.3%
9.4 3109
 
0.3%
9.37 2979
 
0.3%
40.895 2590
 
0.3%
40.66 2520
 
0.3%
Other values (65552) 948667
95.0%
2025-03-26T16:26:41.562371image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 999104
16.0%
3 788291
12.7%
2 616227
9.9%
5 525394
8.4%
7 525040
8.4%
4 501585
8.1%
1 480791
7.7%
6 474958
7.6%
8 472288
7.6%
9 377180
 
6.1%
Other values (3) 469382
7.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6230240
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 999104
16.0%
3 788291
12.7%
2 616227
9.9%
5 525394
8.4%
7 525040
8.4%
4 501585
8.1%
1 480791
7.7%
6 474958
7.6%
8 472288
7.6%
9 377180
 
6.1%
Other values (3) 469382
7.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6230240
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 999104
16.0%
3 788291
12.7%
2 616227
9.9%
5 525394
8.4%
7 525040
8.4%
4 501585
8.1%
1 480791
7.7%
6 474958
7.6%
8 472288
7.6%
9 377180
 
6.1%
Other values (3) 469382
7.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6230240
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 999104
16.0%
3 788291
12.7%
2 616227
9.9%
5 525394
8.4%
7 525040
8.4%
4 501585
8.1%
1 480791
7.7%
6 474958
7.6%
8 472288
7.6%
9 377180
 
6.1%
Other values (3) 469382
7.5%

decimalLongitude
Text

Missing 

Distinct74674
Distinct (%)7.5%
Missing927523
Missing (%)48.1%
Memory size14.7 MiB
2025-03-26T16:26:41.718511image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length8
Mean length7.110716534
Min length3

Characters and Unicode

Total characters7104324
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27322 ?
Unique (%)2.7%

Sample

1st row-73.405
2nd row-83.6297
3rd row-54.742
4th row-66.7708
5th row121.586
ValueCountFrequency (%)
80.1 10531
 
1.1%
127.848 4532
 
0.5%
67.7683 4215
 
0.4%
80.13 3739
 
0.4%
82.7 3518
 
0.4%
67.77 2821
 
0.3%
66.775 2592
 
0.3%
81.6633 2462
 
0.2%
70.6731 2397
 
0.2%
67.755 2356
 
0.2%
Other values (69821) 959938
96.1%
2025-03-26T16:26:41.934451image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 999101
14.1%
- 826292
11.6%
7 744718
10.5%
8 682771
9.6%
1 674748
9.5%
6 575440
8.1%
3 562320
7.9%
2 472661
6.7%
5 433123
6.1%
9 409889
5.8%
Other values (2) 723261
10.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7104324
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 999101
14.1%
- 826292
11.6%
7 744718
10.5%
8 682771
9.6%
1 674748
9.5%
6 575440
8.1%
3 562320
7.9%
2 472661
6.7%
5 433123
6.1%
9 409889
5.8%
Other values (2) 723261
10.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7104324
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 999101
14.1%
- 826292
11.6%
7 744718
10.5%
8 682771
9.6%
1 674748
9.5%
6 575440
8.1%
3 562320
7.9%
2 472661
6.7%
5 433123
6.1%
9 409889
5.8%
Other values (2) 723261
10.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7104324
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 999101
14.1%
- 826292
11.6%
7 744718
10.5%
8 682771
9.6%
1 674748
9.5%
6 575440
8.1%
3 562320
7.9%
2 472661
6.7%
5 433123
6.1%
9 409889
5.8%
Other values (2) 723261
10.2%

geodeticDatum
Text

Missing 

Distinct3
Distinct (%)< 0.1%
Missing1858709
Missing (%)96.5%
Memory size14.7 MiB
2025-03-26T16:26:41.980489image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length5
Mean length5.172038578
Min length5

Characters and Unicode

Total characters351259
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWGS84
2nd rowWGS84
3rd rowWGS84
4th rowWGS84
5th rowWGS84
ValueCountFrequency (%)
wgs84 67016
96.1%
wgs 896
 
1.3%
84 896
 
1.3%
epsg:4326 896
 
1.3%
nad83 3
 
< 0.1%
epsg:4269 3
 
< 0.1%
2025-03-26T16:26:42.065214image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 68811
19.6%
4 68811
19.6%
G 68811
19.6%
8 67915
19.3%
W 67912
19.3%
1795
 
0.5%
3 899
 
0.3%
) 899
 
0.3%
6 899
 
0.3%
2 899
 
0.3%
Other values (8) 3608
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 351259
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
S 68811
19.6%
4 68811
19.6%
G 68811
19.6%
8 67915
19.3%
W 67912
19.3%
1795
 
0.5%
3 899
 
0.3%
) 899
 
0.3%
6 899
 
0.3%
2 899
 
0.3%
Other values (8) 3608
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 351259
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
S 68811
19.6%
4 68811
19.6%
G 68811
19.6%
8 67915
19.3%
W 67912
19.3%
1795
 
0.5%
3 899
 
0.3%
) 899
 
0.3%
6 899
 
0.3%
2 899
 
0.3%
Other values (8) 3608
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 351259
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
S 68811
19.6%
4 68811
19.6%
G 68811
19.6%
8 67915
19.3%
W 67912
19.3%
1795
 
0.5%
3 899
 
0.3%
) 899
 
0.3%
6 899
 
0.3%
2 899
 
0.3%
Other values (8) 3608
 
1.0%

verbatimLatitude
Text

Missing 

Distinct13517
Distinct (%)18.9%
Missing1854954
Missing (%)96.3%
Memory size14.7 MiB
2025-03-26T16:26:42.189507image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length60
Median length39
Mean length9.520092089
Min length1

Characters and Unicode

Total characters682305
Distinct characters57
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6589 ?
Unique (%)9.2%

Sample

1st row12.083197
2nd row35 00.11 N
3rd row21.502905
4th row29 47.5 N
5th row36.4512
ValueCountFrequency (%)
n 42004
 
22.1%
29 8551
 
4.5%
s 7168
 
3.8%
28 6237
 
3.3%
27 6061
 
3.2%
00 3977
 
2.1%
26 2551
 
1.3%
24 2175
 
1.1%
23 1937
 
1.0%
42 1914
 
1.0%
Other values (8710) 107905
56.6%
2025-03-26T16:26:42.391392image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
118810
17.4%
2 70857
10.4%
0 51339
 
7.5%
N 48697
 
7.1%
3 48312
 
7.1%
4 46323
 
6.8%
. 45953
 
6.7%
5 41341
 
6.1%
1 39620
 
5.8%
9 36423
 
5.3%
Other values (47) 134630
19.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 682305
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
118810
17.4%
2 70857
10.4%
0 51339
 
7.5%
N 48697
 
7.1%
3 48312
 
7.1%
4 46323
 
6.8%
. 45953
 
6.7%
5 41341
 
6.1%
1 39620
 
5.8%
9 36423
 
5.3%
Other values (47) 134630
19.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 682305
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
118810
17.4%
2 70857
10.4%
0 51339
 
7.5%
N 48697
 
7.1%
3 48312
 
7.1%
4 46323
 
6.8%
. 45953
 
6.7%
5 41341
 
6.1%
1 39620
 
5.8%
9 36423
 
5.3%
Other values (47) 134630
19.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 682305
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
118810
17.4%
2 70857
10.4%
0 51339
 
7.5%
N 48697
 
7.1%
3 48312
 
7.1%
4 46323
 
6.8%
. 45953
 
6.7%
5 41341
 
6.1%
1 39620
 
5.8%
9 36423
 
5.3%
Other values (47) 134630
19.7%

verbatimLongitude
Text

Missing 

Distinct13852
Distinct (%)19.3%
Missing1855011
Missing (%)96.3%
Memory size14.7 MiB
2025-03-26T16:26:42.521580image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length59
Median length40
Mean length10.08015304
Min length2

Characters and Unicode

Total characters721870
Distinct characters59
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6898 ?
Unique (%)9.6%

Sample

1st row-68.899058
2nd row139 13.45 E
3rd row-157.801784
4th row85 54.5 W
5th row-121.1546
ValueCountFrequency (%)
w 42780
 
22.5%
84 7567
 
4.0%
e 6275
 
3.3%
00 3969
 
2.1%
83 3206
 
1.7%
86 2759
 
1.5%
85 1732
 
0.9%
53 1631
 
0.9%
79 1577
 
0.8%
17 1288
 
0.7%
Other values (8986) 117372
61.7%
2025-03-26T16:26:42.712850image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
118543
16.4%
0 65223
9.0%
1 63954
8.9%
8 51398
 
7.1%
W 49354
 
6.8%
. 48219
 
6.7%
5 47291
 
6.6%
2 42186
 
5.8%
3 42161
 
5.8%
4 41325
 
5.7%
Other values (49) 152216
21.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 721870
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
118543
16.4%
0 65223
9.0%
1 63954
8.9%
8 51398
 
7.1%
W 49354
 
6.8%
. 48219
 
6.7%
5 47291
 
6.6%
2 42186
 
5.8%
3 42161
 
5.8%
4 41325
 
5.7%
Other values (49) 152216
21.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 721870
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
118543
16.4%
0 65223
9.0%
1 63954
8.9%
8 51398
 
7.1%
W 49354
 
6.8%
. 48219
 
6.7%
5 47291
 
6.6%
2 42186
 
5.8%
3 42161
 
5.8%
4 41325
 
5.7%
Other values (49) 152216
21.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 721870
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
118543
16.4%
0 65223
9.0%
1 63954
8.9%
8 51398
 
7.1%
W 49354
 
6.8%
. 48219
 
6.7%
5 47291
 
6.6%
2 42186
 
5.8%
3 42161
 
5.8%
4 41325
 
5.7%
Other values (49) 152216
21.1%
Distinct9
Distinct (%)< 0.1%
Missing1247024
Missing (%)64.7%
Memory size14.7 MiB
2025-03-26T16:26:42.747523image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length23
Mean length22.60570041
Min length3

Characters and Unicode

Total characters15362834
Distinct characters30
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowDegrees Minutes Seconds
2nd rowDegrees Minutes Seconds
3rd rowDegrees Minutes Seconds
4th rowDegrees Minutes Seconds
5th rowDegrees Minutes Seconds
ValueCountFrequency (%)
degrees 670992
33.4%
minutes 648285
32.3%
seconds 648285
32.3%
decimal 22707
 
1.1%
township 7004
 
0.3%
range 7004
 
0.3%
marsden 605
 
< 0.1%
square 605
 
< 0.1%
unknown 532
 
< 0.1%
utm 464
 
< 0.1%
Other values (3) 6
 
< 0.1%
2025-03-26T16:26:42.841495image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 3340468
21.7%
s 1975171
12.9%
1326889
 
8.6%
n 1312779
 
8.5%
g 677996
 
4.4%
i 677996
 
4.4%
r 672205
 
4.4%
d 671555
 
4.4%
D 671037
 
4.4%
c 670993
 
4.4%
Other values (20) 3365745
21.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 15362834
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 3340468
21.7%
s 1975171
12.9%
1326889
 
8.6%
n 1312779
 
8.5%
g 677996
 
4.4%
i 677996
 
4.4%
r 672205
 
4.4%
d 671555
 
4.4%
D 671037
 
4.4%
c 670993
 
4.4%
Other values (20) 3365745
21.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 15362834
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 3340468
21.7%
s 1975171
12.9%
1326889
 
8.6%
n 1312779
 
8.5%
g 677996
 
4.4%
i 677996
 
4.4%
r 672205
 
4.4%
d 671555
 
4.4%
D 671037
 
4.4%
c 670993
 
4.4%
Other values (20) 3365745
21.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 15362834
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 3340468
21.7%
s 1975171
12.9%
1326889
 
8.6%
n 1312779
 
8.5%
g 677996
 
4.4%
i 677996
 
4.4%
r 672205
 
4.4%
d 671555
 
4.4%
D 671037
 
4.4%
c 670993
 
4.4%
Other values (20) 3365745
21.9%

georeferenceProtocol
Text

Missing 

Distinct112
Distinct (%)< 0.1%
Missing1265938
Missing (%)65.7%
Memory size14.7 MiB
2025-03-26T16:26:42.874497image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length87
Median length20
Mean length20.10033511
Min length3

Characters and Unicode

Total characters13280010
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)< 0.1%

Sample

1st rowunknown, from legacy
2nd rowunknown, from legacy
3rd rowunknown, from legacy
4th rowunknown, from legacy
5th rowunknown, from legacy
ValueCountFrequency (%)
from 509129
26.2%
unknown 507646
26.1%
legacy 505194
26.0%
geolocate 70318
 
3.6%
names 41944
 
2.2%
geographic 41563
 
2.1%
of 35286
 
1.8%
getty 34694
 
1.8%
thesaurus 34693
 
1.8%
may 23195
 
1.2%
Other values (124) 141522
 
7.3%
2025-03-26T16:26:43.050830image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 1561014
 
11.8%
1284498
 
9.7%
o 1253557
 
9.4%
e 822152
 
6.2%
a 797127
 
6.0%
r 642108
 
4.8%
c 624730
 
4.7%
g 591375
 
4.5%
u 580832
 
4.4%
y 577503
 
4.3%
Other values (54) 4545114
34.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13280010
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 1561014
 
11.8%
1284498
 
9.7%
o 1253557
 
9.4%
e 822152
 
6.2%
a 797127
 
6.0%
r 642108
 
4.8%
c 624730
 
4.7%
g 591375
 
4.5%
u 580832
 
4.4%
y 577503
 
4.3%
Other values (54) 4545114
34.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13280010
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 1561014
 
11.8%
1284498
 
9.7%
o 1253557
 
9.4%
e 822152
 
6.2%
a 797127
 
6.0%
r 642108
 
4.8%
c 624730
 
4.7%
g 591375
 
4.5%
u 580832
 
4.4%
y 577503
 
4.3%
Other values (54) 4545114
34.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13280010
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 1561014
 
11.8%
1284498
 
9.7%
o 1253557
 
9.4%
e 822152
 
6.2%
a 797127
 
6.0%
r 642108
 
4.8%
c 624730
 
4.7%
g 591375
 
4.5%
u 580832
 
4.4%
y 577503
 
4.3%
Other values (54) 4545114
34.2%

georeferenceRemarks
Text

Missing 

Distinct4821
Distinct (%)15.9%
Missing1896335
Missing (%)98.4%
Memory size14.7 MiB
2025-03-26T16:26:43.176549image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length122
Median length118
Mean length23.03743933
Min length1

Characters and Unicode

Total characters697781
Distinct characters78
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3164 ?
Unique (%)10.4%

Sample

1st rowExtended About 16 Km Offshore From Crystal River Power Plant
2nd row0.8 mile west of Montgomery-Polk county line, north side of
3rd rowSan Andreas Fault
4th row6 Mile W Of Watsonville
5th rowfrom Holt data card
ValueCountFrequency (%)
approximate 9789
 
8.9%
from 6478
 
5.9%
river 3465
 
3.2%
of 3099
 
2.8%
about 3076
 
2.8%
16 2974
 
2.7%
km 2970
 
2.7%
plant 2933
 
2.7%
power 2929
 
2.7%
offshore 2929
 
2.7%
Other values (4967) 68763
62.9%
2025-03-26T16:26:43.381459image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
79116
 
11.3%
a 60521
 
8.7%
e 55652
 
8.0%
o 49199
 
7.1%
r 47507
 
6.8%
t 40250
 
5.8%
i 29472
 
4.2%
n 26683
 
3.8%
p 24673
 
3.5%
m 24235
 
3.5%
Other values (68) 260473
37.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 697781
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
79116
 
11.3%
a 60521
 
8.7%
e 55652
 
8.0%
o 49199
 
7.1%
r 47507
 
6.8%
t 40250
 
5.8%
i 29472
 
4.2%
n 26683
 
3.8%
p 24673
 
3.5%
m 24235
 
3.5%
Other values (68) 260473
37.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 697781
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
79116
 
11.3%
a 60521
 
8.7%
e 55652
 
8.0%
o 49199
 
7.1%
r 47507
 
6.8%
t 40250
 
5.8%
i 29472
 
4.2%
n 26683
 
3.8%
p 24673
 
3.5%
m 24235
 
3.5%
Other values (68) 260473
37.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 697781
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
79116
 
11.3%
a 60521
 
8.7%
e 55652
 
8.0%
o 49199
 
7.1%
r 47507
 
6.8%
t 40250
 
5.8%
i 29472
 
4.2%
n 26683
 
3.8%
p 24673
 
3.5%
m 24235
 
3.5%
Other values (68) 260473
37.3%
Distinct5
Distinct (%)< 0.1%
Missing1908487
Missing (%)99.1%
Memory size14.7 MiB
2025-03-26T16:26:43.419966image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.54799581
Min length3

Characters and Unicode

Total characters64350
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowcf.
2nd rowcf.
3rd rowuncertain
4th rowcf.
5th rowcf.
ValueCountFrequency (%)
cf 15643
86.2%
uncertain 1489
 
8.2%
aff 600
 
3.3%
near 405
 
2.2%
2025-03-26T16:26:43.512476image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 17132
26.6%
f 16843
26.2%
. 16243
25.2%
n 3383
 
5.3%
a 2494
 
3.9%
e 1894
 
2.9%
r 1894
 
2.9%
t 1489
 
2.3%
i 1489
 
2.3%
u 1487
 
2.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 64350
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
c 17132
26.6%
f 16843
26.2%
. 16243
25.2%
n 3383
 
5.3%
a 2494
 
3.9%
e 1894
 
2.9%
r 1894
 
2.9%
t 1489
 
2.3%
i 1489
 
2.3%
u 1487
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 64350
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
c 17132
26.6%
f 16843
26.2%
. 16243
25.2%
n 3383
 
5.3%
a 2494
 
3.9%
e 1894
 
2.9%
r 1894
 
2.9%
t 1489
 
2.3%
i 1489
 
2.3%
u 1487
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 64350
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
c 17132
26.6%
f 16843
26.2%
. 16243
25.2%
n 3383
 
5.3%
a 2494
 
3.9%
e 1894
 
2.9%
r 1894
 
2.9%
t 1489
 
2.3%
i 1489
 
2.3%
u 1487
 
2.3%

typeStatus
Text

Missing 

Distinct92
Distinct (%)0.1%
Missing1838784
Missing (%)95.4%
Memory size14.7 MiB
2025-03-26T16:26:43.545339image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length40
Median length8
Mean length7.997381603
Min length4

Characters and Unicode

Total characters702490
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)< 0.1%

Sample

1st rowParatype
2nd rowHolotype
3rd rowParatype
4th rowHolotype
5th rowParatype
ValueCountFrequency (%)
paratype 41431
45.6%
holotype 26120
28.7%
syntype 10065
 
11.1%
type 5402
 
5.9%
allotype 3095
 
3.4%
paralectotype 1159
 
1.3%
1105
 
1.2%
lectotype 1071
 
1.2%
neotype 306
 
0.3%
unconfirmed 292
 
0.3%
Other values (18) 895
 
1.0%
2025-03-26T16:26:43.649379image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
y 99712
14.2%
e 92432
13.2%
p 90056
12.8%
t 87239
12.4%
a 86600
12.3%
o 59523
8.5%
P 43207
6.2%
r 43149
6.1%
l 33478
 
4.8%
H 26368
 
3.8%
Other values (17) 40726
5.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 702490
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
y 99712
14.2%
e 92432
13.2%
p 90056
12.8%
t 87239
12.4%
a 86600
12.3%
o 59523
8.5%
P 43207
6.2%
r 43149
6.1%
l 33478
 
4.8%
H 26368
 
3.8%
Other values (17) 40726
5.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 702490
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
y 99712
14.2%
e 92432
13.2%
p 90056
12.8%
t 87239
12.4%
a 86600
12.3%
o 59523
8.5%
P 43207
6.2%
r 43149
6.1%
l 33478
 
4.8%
H 26368
 
3.8%
Other values (17) 40726
5.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 702490
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
y 99712
14.2%
e 92432
13.2%
p 90056
12.8%
t 87239
12.4%
a 86600
12.3%
o 59523
8.5%
P 43207
6.2%
r 43149
6.1%
l 33478
 
4.8%
H 26368
 
3.8%
Other values (17) 40726
5.8%

identifiedBy
Text

Missing 

Distinct13460
Distinct (%)1.6%
Missing1085347
Missing (%)56.3%
Memory size14.7 MiB
2025-03-26T16:26:43.780236image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length226
Median length133
Mean length38.24108944
Min length2

Characters and Unicode

Total characters32171349
Distinct characters94
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4200 ?
Unique (%)0.5%

Sample

1st rowOpresko, Dennis M., Oak Ridge National Laboratory (UNITED STATES)
2nd rowNance
3rd rowMah, Christopher, (IZ), Smithsonian Institution - National Museum of Natural History (UNITED STATES)
4th rowVerrill, Addison E., Peabody Museum, Yale
5th rowJudkins, D.
ValueCountFrequency (%)
of 247224
 
5.3%
museum 200664
 
4.3%
national 197148
 
4.2%
institution 188610
 
4.1%
smithsonian 186080
 
4.0%
natural 185797
 
4.0%
history 185443
 
4.0%
united 130434
 
2.8%
states 129664
 
2.8%
87212
 
1.9%
Other values (9432) 2904588
62.6%
2025-03-26T16:26:43.989461image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3801587
 
11.8%
a 2080752
 
6.5%
i 2056464
 
6.4%
t 2013428
 
6.3%
n 1896268
 
5.9%
o 1745003
 
5.4%
e 1500286
 
4.7%
r 1385073
 
4.3%
s 1382904
 
4.3%
, 1349528
 
4.2%
Other values (84) 12960056
40.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 32171349
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3801587
 
11.8%
a 2080752
 
6.5%
i 2056464
 
6.4%
t 2013428
 
6.3%
n 1896268
 
5.9%
o 1745003
 
5.4%
e 1500286
 
4.7%
r 1385073
 
4.3%
s 1382904
 
4.3%
, 1349528
 
4.2%
Other values (84) 12960056
40.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 32171349
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3801587
 
11.8%
a 2080752
 
6.5%
i 2056464
 
6.4%
t 2013428
 
6.3%
n 1896268
 
5.9%
o 1745003
 
5.4%
e 1500286
 
4.7%
r 1385073
 
4.3%
s 1382904
 
4.3%
, 1349528
 
4.2%
Other values (84) 12960056
40.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 32171349
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3801587
 
11.8%
a 2080752
 
6.5%
i 2056464
 
6.4%
t 2013428
 
6.3%
n 1896268
 
5.9%
o 1745003
 
5.4%
e 1500286
 
4.7%
r 1385073
 
4.3%
s 1382904
 
4.3%
, 1349528
 
4.2%
Other values (84) 12960056
40.3%

scientificName
Text

Missing 

Distinct134002
Distinct (%)8.5%
Missing353809
Missing (%)18.4%
Memory size14.7 MiB
2025-03-26T16:26:44.159793image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length85
Median length59
Mean length19.44694195
Min length4

Characters and Unicode

Total characters30586442
Distinct characters78
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51619 ?
Unique (%)3.3%

Sample

1st rowScypha sp.
2nd rowBulla striata
3rd rowStylopathes columnaris
4th rowOphiothrix suensonii
5th rowCypraea labrolineata
ValueCountFrequency (%)
sp 198081
 
6.0%
conus 24331
 
0.7%
cypraea 15397
 
0.5%
cambarus 12004
 
0.4%
cerithium 9397
 
0.3%
orconectes 8684
 
0.3%
procambarus 8141
 
0.2%
nassarius 6728
 
0.2%
gracilis 6633
 
0.2%
terebra 5169
 
0.2%
Other values (70833) 3025603
91.1%
2025-03-26T16:26:44.401556image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3610881
 
11.8%
i 2750781
 
9.0%
s 2277818
 
7.4%
e 1954597
 
6.4%
r 1901572
 
6.2%
o 1840828
 
6.0%
1747353
 
5.7%
l 1714474
 
5.6%
n 1541916
 
5.0%
t 1537414
 
5.0%
Other values (68) 9708808
31.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 30586442
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 3610881
 
11.8%
i 2750781
 
9.0%
s 2277818
 
7.4%
e 1954597
 
6.4%
r 1901572
 
6.2%
o 1840828
 
6.0%
1747353
 
5.7%
l 1714474
 
5.6%
n 1541916
 
5.0%
t 1537414
 
5.0%
Other values (68) 9708808
31.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 30586442
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 3610881
 
11.8%
i 2750781
 
9.0%
s 2277818
 
7.4%
e 1954597
 
6.4%
r 1901572
 
6.2%
o 1840828
 
6.0%
1747353
 
5.7%
l 1714474
 
5.6%
n 1541916
 
5.0%
t 1537414
 
5.0%
Other values (68) 9708808
31.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 30586442
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 3610881
 
11.8%
i 2750781
 
9.0%
s 2277818
 
7.4%
e 1954597
 
6.4%
r 1901572
 
6.2%
o 1840828
 
6.0%
1747353
 
5.7%
l 1714474
 
5.6%
n 1541916
 
5.0%
t 1537414
 
5.0%
Other values (68) 9708808
31.7%
Distinct4354
Distinct (%)0.2%
Missing463
Missing (%)< 0.1%
Memory size14.7 MiB
2025-03-26T16:26:44.540967image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length134
Median length117
Mean length62.96731841
Min length7

Characters and Unicode

Total characters121285193
Distinct characters60
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique586 ?
Unique (%)< 0.1%

Sample

1st rowAnimalia, Porifera, Calcarea
2nd rowAnimalia, Mollusca, Gastropoda, Bullidae
3rd rowAnimalia, Cnidaria, Anthozoa, Hexacorallia, Antipatharia, Stylopathidae
4th rowAnimalia, Echinodermata, Ophiuroidea, Ophiurida, Ophiotrichidae
5th rowAnimalia, Mollusca, Gastropoda, Cypraeidae
ValueCountFrequency (%)
animalia 1922281
 
18.1%
mollusca 866530
 
8.1%
gastropoda 612846
 
5.8%
arthropoda 390799
 
3.7%
crustacea 385157
 
3.6%
malacostraca 302012
 
2.8%
eumalacostraca 294932
 
2.8%
annelida 241826
 
2.3%
polychaeta 212990
 
2.0%
bivalvia 207715
 
2.0%
Other values (4342) 5203403
48.9%
2025-03-26T16:26:44.762252image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 19362928
16.0%
i 10630715
 
8.8%
8714330
 
7.2%
, 8692786
 
7.2%
o 7924786
 
6.5%
l 7527157
 
6.2%
e 6163584
 
5.1%
d 5675931
 
4.7%
r 5613322
 
4.6%
c 5024415
 
4.1%
Other values (50) 35955239
29.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 121285193
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 19362928
16.0%
i 10630715
 
8.8%
8714330
 
7.2%
, 8692786
 
7.2%
o 7924786
 
6.5%
l 7527157
 
6.2%
e 6163584
 
5.1%
d 5675931
 
4.7%
r 5613322
 
4.6%
c 5024415
 
4.1%
Other values (50) 35955239
29.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 121285193
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 19362928
16.0%
i 10630715
 
8.8%
8714330
 
7.2%
, 8692786
 
7.2%
o 7924786
 
6.5%
l 7527157
 
6.2%
e 6163584
 
5.1%
d 5675931
 
4.7%
r 5613322
 
4.6%
c 5024415
 
4.1%
Other values (50) 35955239
29.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 121285193
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 19362928
16.0%
i 10630715
 
8.8%
8714330
 
7.2%
, 8692786
 
7.2%
o 7924786
 
6.5%
l 7527157
 
6.2%
e 6163584
 
5.1%
d 5675931
 
4.7%
r 5613322
 
4.6%
c 5024415
 
4.1%
Other values (50) 35955239
29.6%
Distinct7
Distinct (%)< 0.1%
Missing2063
Missing (%)0.1%
Memory size14.7 MiB
2025-03-26T16:26:44.806308image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length8
Mean length8.000021304
Min length7

Characters and Unicode

Total characters15396529
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowAnimalia
2nd rowAnimalia
3rd rowAnimalia
4th rowAnimalia
5th rowAnimalia
ValueCountFrequency (%)
animalia 1922281
99.9%
protozoa 2154
 
0.1%
protista 55
 
< 0.1%
chromista 36
 
< 0.1%
bacteria 28
 
< 0.1%
eukaryota 6
 
< 0.1%
eukarya 1
 
< 0.1%
2025-03-26T16:26:44.892652image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3846877
25.0%
i 3844681
25.0%
m 1922317
12.5%
A 1922281
12.5%
n 1922281
12.5%
l 1922281
12.5%
o 6559
 
< 0.1%
t 2334
 
< 0.1%
r 2280
 
< 0.1%
P 2209
 
< 0.1%
Other values (11) 2429
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 15396529
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 3846877
25.0%
i 3844681
25.0%
m 1922317
12.5%
A 1922281
12.5%
n 1922281
12.5%
l 1922281
12.5%
o 6559
 
< 0.1%
t 2334
 
< 0.1%
r 2280
 
< 0.1%
P 2209
 
< 0.1%
Other values (11) 2429
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 15396529
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 3846877
25.0%
i 3844681
25.0%
m 1922317
12.5%
A 1922281
12.5%
n 1922281
12.5%
l 1922281
12.5%
o 6559
 
< 0.1%
t 2334
 
< 0.1%
r 2280
 
< 0.1%
P 2209
 
< 0.1%
Other values (11) 2429
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 15396529
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 3846877
25.0%
i 3844681
25.0%
m 1922317
12.5%
A 1922281
12.5%
n 1922281
12.5%
l 1922281
12.5%
o 6559
 
< 0.1%
t 2334
 
< 0.1%
r 2280
 
< 0.1%
P 2209
 
< 0.1%
Other values (11) 2429
 
< 0.1%

phylum
Text

Distinct83
Distinct (%)< 0.1%
Missing510
Missing (%)< 0.1%
Memory size14.7 MiB
2025-03-26T16:26:44.923970image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length8
Mean length8.859794903
Min length6

Characters and Unicode

Total characters17064975
Distinct characters47
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)< 0.1%

Sample

1st rowPorifera
2nd rowMollusca
3rd rowCnidaria
4th rowEchinodermata
5th rowMollusca
ValueCountFrequency (%)
mollusca 866530
45.0%
arthropoda 390799
20.3%
annelida 241669
 
12.5%
cnidaria 117405
 
6.1%
echinodermata 91219
 
4.7%
nematoda 68788
 
3.6%
platyhelminthes 46021
 
2.4%
porifera 32731
 
1.7%
chordata 19752
 
1.0%
sipuncula 10417
 
0.5%
Other values (83) 42159
 
2.2%
2025-03-26T16:26:45.014476image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2242458
13.1%
l 2086204
12.2%
o 1908974
11.2%
r 1108230
 
6.5%
c 989500
 
5.8%
d 934375
 
5.5%
s 915559
 
5.4%
u 888208
 
5.2%
M 867324
 
5.1%
n 771161
 
4.5%
Other values (37) 4352982
25.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17064975
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2242458
13.1%
l 2086204
12.2%
o 1908974
11.2%
r 1108230
 
6.5%
c 989500
 
5.8%
d 934375
 
5.5%
s 915559
 
5.4%
u 888208
 
5.2%
M 867324
 
5.1%
n 771161
 
4.5%
Other values (37) 4352982
25.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17064975
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2242458
13.1%
l 2086204
12.2%
o 1908974
11.2%
r 1108230
 
6.5%
c 989500
 
5.8%
d 934375
 
5.5%
s 915559
 
5.4%
u 888208
 
5.2%
M 867324
 
5.1%
n 771161
 
4.5%
Other values (37) 4352982
25.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17064975
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2242458
13.1%
l 2086204
12.2%
o 1908974
11.2%
r 1108230
 
6.5%
c 989500
 
5.8%
d 934375
 
5.5%
s 915559
 
5.4%
u 888208
 
5.2%
M 867324
 
5.1%
n 771161
 
4.5%
Other values (37) 4352982
25.5%

class
Text

Missing 

Distinct140
Distinct (%)< 0.1%
Missing76143
Missing (%)4.0%
Memory size14.7 MiB
2025-03-26T16:26:45.051804image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length19
Mean length10.09883268
Min length4

Characters and Unicode

Total characters18687698
Distinct characters43
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)< 0.1%

Sample

1st rowCalcarea
2nd rowGastropoda
3rd rowAnthozoa
4th rowOphiuroidea
5th rowGastropoda
ValueCountFrequency (%)
gastropoda 612846
33.1%
malacostraca 302012
16.3%
polychaeta 210949
 
11.4%
bivalvia 207715
 
11.2%
anthozoa 93066
 
5.0%
maxillopoda 54379
 
2.9%
chromadorea 34767
 
1.9%
ophiuroidea 27086
 
1.5%
asteroidea 25639
 
1.4%
oligochaeta 25301
 
1.4%
Other values (130) 256721
13.9%
2025-03-26T16:26:45.156186image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4040939
21.6%
o 2551649
13.7%
t 1353841
 
7.2%
r 1171557
 
6.3%
s 1019801
 
5.5%
c 959881
 
5.1%
d 951317
 
5.1%
l 934300
 
5.0%
p 820306
 
4.4%
i 731119
 
3.9%
Other values (33) 4152988
22.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 18687698
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 4040939
21.6%
o 2551649
13.7%
t 1353841
 
7.2%
r 1171557
 
6.3%
s 1019801
 
5.5%
c 959881
 
5.1%
d 951317
 
5.1%
l 934300
 
5.0%
p 820306
 
4.4%
i 731119
 
3.9%
Other values (33) 4152988
22.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 18687698
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 4040939
21.6%
o 2551649
13.7%
t 1353841
 
7.2%
r 1171557
 
6.3%
s 1019801
 
5.5%
c 959881
 
5.1%
d 951317
 
5.1%
l 934300
 
5.0%
p 820306
 
4.4%
i 731119
 
3.9%
Other values (33) 4152988
22.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 18687698
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 4040939
21.6%
o 2551649
13.7%
t 1353841
 
7.2%
r 1171557
 
6.3%
s 1019801
 
5.5%
c 959881
 
5.1%
d 951317
 
5.1%
l 934300
 
5.0%
p 820306
 
4.4%
i 731119
 
3.9%
Other values (33) 4152988
22.2%

order
Text

Missing 

Distinct464
Distinct (%)< 0.1%
Missing941076
Missing (%)48.8%
Memory size14.7 MiB
2025-03-26T16:26:45.284895image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length28
Median length21
Mean length10.13112806
Min length5

Characters and Unicode

Total characters9984713
Distinct characters50
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)< 0.1%

Sample

1st rowAntipatharia
2nd rowOphiurida
3rd rowForcipulatida
4th rowForcipulatida
5th rowDecapoda
ValueCountFrequency (%)
decapoda 196756
20.0%
phyllodocida 69322
 
7.0%
scleractinia 54216
 
5.5%
amphipoda 49537
 
5.0%
isopoda 29009
 
2.9%
terebellida 28672
 
2.9%
unionoida 28564
 
2.9%
eunicida 25639
 
2.6%
ophiurida 22913
 
2.3%
calanoida 21063
 
2.1%
Other values (456) 460027
46.7%
2025-03-26T16:26:45.482973image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1614028
16.2%
o 1058752
10.6%
i 1001000
10.0%
d 988699
9.9%
c 644887
 
6.5%
e 615629
 
6.2%
p 533947
 
5.3%
l 509666
 
5.1%
n 359874
 
3.6%
r 349534
 
3.5%
Other values (40) 2308697
23.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9984713
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1614028
16.2%
o 1058752
10.6%
i 1001000
10.0%
d 988699
9.9%
c 644887
 
6.5%
e 615629
 
6.2%
p 533947
 
5.3%
l 509666
 
5.1%
n 359874
 
3.6%
r 349534
 
3.5%
Other values (40) 2308697
23.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9984713
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1614028
16.2%
o 1058752
10.6%
i 1001000
10.0%
d 988699
9.9%
c 644887
 
6.5%
e 615629
 
6.2%
p 533947
 
5.3%
l 509666
 
5.1%
n 359874
 
3.6%
r 349534
 
3.5%
Other values (40) 2308697
23.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9984713
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1614028
16.2%
o 1058752
10.6%
i 1001000
10.0%
d 988699
9.9%
c 644887
 
6.5%
e 615629
 
6.2%
p 533947
 
5.3%
l 509666
 
5.1%
n 359874
 
3.6%
r 349534
 
3.5%
Other values (40) 2308697
23.1%

family
Text

Missing 

Distinct3009
Distinct (%)0.2%
Missing191873
Missing (%)10.0%
Memory size14.7 MiB
2025-03-26T16:26:45.596655image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length27
Median length23
Mean length11.08733415
Min length6

Characters and Unicode

Total characters19233764
Distinct characters55
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique298 ?
Unique (%)< 0.1%

Sample

1st rowBullidae
2nd rowStylopathidae
3rd rowOphiotrichidae
4th rowCypraeidae
5th rowAsteriidae
ValueCountFrequency (%)
conidae 38827
 
2.2%
cambaridae 29326
 
1.7%
unionidae 26844
 
1.5%
veneridae 17892
 
1.0%
trochidae 16927
 
1.0%
cerithiidae 16899
 
1.0%
cypraeidae 16835
 
1.0%
spionidae 15851
 
0.9%
buccinidae 15342
 
0.9%
syllidae 14116
 
0.8%
Other values (2998) 1526031
88.0%
2025-03-26T16:26:45.784482image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 2891000
15.0%
a 2634956
13.7%
e 2543276
13.2%
d 1977649
10.3%
r 977348
 
5.1%
l 957729
 
5.0%
o 948135
 
4.9%
n 841316
 
4.4%
t 631758
 
3.3%
c 541009
 
2.8%
Other values (45) 4289588
22.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19233764
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 2891000
15.0%
a 2634956
13.7%
e 2543276
13.2%
d 1977649
10.3%
r 977348
 
5.1%
l 957729
 
5.0%
o 948135
 
4.9%
n 841316
 
4.4%
t 631758
 
3.3%
c 541009
 
2.8%
Other values (45) 4289588
22.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19233764
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 2891000
15.0%
a 2634956
13.7%
e 2543276
13.2%
d 1977649
10.3%
r 977348
 
5.1%
l 957729
 
5.0%
o 948135
 
4.9%
n 841316
 
4.4%
t 631758
 
3.3%
c 541009
 
2.8%
Other values (45) 4289588
22.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19233764
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 2891000
15.0%
a 2634956
13.7%
e 2543276
13.2%
d 1977649
10.3%
r 977348
 
5.1%
l 957729
 
5.0%
o 948135
 
4.9%
n 841316
 
4.4%
t 631758
 
3.3%
c 541009
 
2.8%
Other values (45) 4289588
22.3%

genus
Text

Missing 

Distinct21651
Distinct (%)1.4%
Missing353985
Missing (%)18.4%
Memory size14.7 MiB
2025-03-26T16:26:45.936938image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length27
Median length23
Mean length9.304563221
Min length2

Characters and Unicode

Total characters14632719
Distinct characters56
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4272 ?
Unique (%)0.3%

Sample

1st rowScypha
2nd rowBulla
3rd rowStylopathes
4th rowOphiothrix
5th rowCypraea
ValueCountFrequency (%)
conus 24255
 
1.5%
cypraea 15397
 
1.0%
cambarus 10446
 
0.7%
cerithium 9396
 
0.6%
orconectes 8666
 
0.6%
procambarus 8129
 
0.5%
nassarius 6727
 
0.4%
lumbrineris 4967
 
0.3%
terebra 4966
 
0.3%
aricidea 4582
 
0.3%
Other values (21642) 1475130
93.8%
2025-03-26T16:26:46.151863image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1748035
 
11.9%
i 1266283
 
8.7%
o 1158096
 
7.9%
e 1018760
 
7.0%
r 970388
 
6.6%
s 940310
 
6.4%
l 916823
 
6.3%
t 707677
 
4.8%
n 704705
 
4.8%
u 688969
 
4.7%
Other values (46) 4512673
30.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14632719
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1748035
 
11.9%
i 1266283
 
8.7%
o 1158096
 
7.9%
e 1018760
 
7.0%
r 970388
 
6.6%
s 940310
 
6.4%
l 916823
 
6.3%
t 707677
 
4.8%
n 704705
 
4.8%
u 688969
 
4.7%
Other values (46) 4512673
30.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14632719
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1748035
 
11.9%
i 1266283
 
8.7%
o 1158096
 
7.9%
e 1018760
 
7.0%
r 970388
 
6.6%
s 940310
 
6.4%
l 916823
 
6.3%
t 707677
 
4.8%
n 704705
 
4.8%
u 688969
 
4.7%
Other values (46) 4512673
30.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14632719
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1748035
 
11.9%
i 1266283
 
8.7%
o 1158096
 
7.9%
e 1018760
 
7.0%
r 970388
 
6.6%
s 940310
 
6.4%
l 916823
 
6.3%
t 707677
 
4.8%
n 704705
 
4.8%
u 688969
 
4.7%
Other values (46) 4512673
30.8%

subgenus
Text

Missing 

Distinct2864
Distinct (%)2.5%
Missing1813855
Missing (%)94.1%
Memory size14.7 MiB
2025-03-26T16:26:46.278836image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length16
Mean length10.25055645
Min length3

Characters and Unicode

Total characters1155945
Distinct characters52
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique738 ?
Unique (%)0.7%

Sample

1st rowOrtmannicus
2nd rowTorquis
3rd rowScolelepis
4th rowCaryophyllia
5th rowPitarenus
ValueCountFrequency (%)
thericium 3471
 
3.1%
depressicambarus 2960
 
2.6%
ortmannicus 2587
 
2.3%
stephanoconus 2431
 
2.2%
cambarus 1558
 
1.4%
canarium 1428
 
1.3%
nebularia 1392
 
1.2%
costellaria 1392
 
1.2%
strigatella 1336
 
1.2%
pennides 1328
 
1.2%
Other values (2854) 92886
82.4%
2025-03-26T16:26:46.549999image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 138899
12.0%
i 104756
 
9.1%
o 86575
 
7.5%
r 84945
 
7.3%
s 80353
 
7.0%
l 69346
 
6.0%
e 68863
 
6.0%
u 66074
 
5.7%
n 64739
 
5.6%
t 53461
 
4.6%
Other values (42) 337934
29.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1155945
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 138899
12.0%
i 104756
 
9.1%
o 86575
 
7.5%
r 84945
 
7.3%
s 80353
 
7.0%
l 69346
 
6.0%
e 68863
 
6.0%
u 66074
 
5.7%
n 64739
 
5.6%
t 53461
 
4.6%
Other values (42) 337934
29.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1155945
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 138899
12.0%
i 104756
 
9.1%
o 86575
 
7.5%
r 84945
 
7.3%
s 80353
 
7.0%
l 69346
 
6.0%
e 68863
 
6.0%
u 66074
 
5.7%
n 64739
 
5.6%
t 53461
 
4.6%
Other values (42) 337934
29.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1155945
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 138899
12.0%
i 104756
 
9.1%
o 86575
 
7.5%
r 84945
 
7.3%
s 80353
 
7.0%
l 69346
 
6.0%
e 68863
 
6.0%
u 66074
 
5.7%
n 64739
 
5.6%
t 53461
 
4.6%
Other values (42) 337934
29.2%

specificEpithet
Text

Missing 

Distinct46665
Distinct (%)3.0%
Missing354023
Missing (%)18.4%
Memory size14.7 MiB
2025-03-26T16:26:46.705312image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length22
Median length19
Mean length7.82675135
Min length1

Characters and Unicode

Total characters12308357
Distinct characters46
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13435 ?
Unique (%)0.9%

Sample

1st rowsp.
2nd rowstriata
3rd rowcolumnaris
4th rowsuensonii
5th rowlabrolineata
ValueCountFrequency (%)
sp 198067
 
12.6%
gracilis 6362
 
0.4%
affinis 3602
 
0.2%
fragilis 3505
 
0.2%
elegans 3414
 
0.2%
aculeata 3110
 
0.2%
borealis 2991
 
0.2%
americanus 2825
 
0.2%
grandis 2553
 
0.2%
tenuis 2439
 
0.2%
Other values (46637) 1345134
85.5%
2025-03-26T16:26:46.913790image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1648893
13.4%
i 1322796
10.7%
s 1208959
9.8%
e 828874
 
6.7%
r 813334
 
6.6%
t 747348
 
6.1%
u 735729
 
6.0%
n 734796
 
6.0%
l 699924
 
5.7%
c 585231
 
4.8%
Other values (36) 2982473
24.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12308357
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1648893
13.4%
i 1322796
10.7%
s 1208959
9.8%
e 828874
 
6.7%
r 813334
 
6.6%
t 747348
 
6.1%
u 735729
 
6.0%
n 734796
 
6.0%
l 699924
 
5.7%
c 585231
 
4.8%
Other values (36) 2982473
24.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12308357
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1648893
13.4%
i 1322796
10.7%
s 1208959
9.8%
e 828874
 
6.7%
r 813334
 
6.6%
t 747348
 
6.1%
u 735729
 
6.0%
n 734796
 
6.0%
l 699924
 
5.7%
c 585231
 
4.8%
Other values (36) 2982473
24.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12308357
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1648893
13.4%
i 1322796
10.7%
s 1208959
9.8%
e 828874
 
6.7%
r 813334
 
6.6%
t 747348
 
6.1%
u 735729
 
6.0%
n 734796
 
6.0%
l 699924
 
5.7%
c 585231
 
4.8%
Other values (36) 2982473
24.2%

infraspecificEpithet
Text

Missing 

Distinct6143
Distinct (%)10.4%
Missing1867459
Missing (%)96.9%
Memory size14.7 MiB
2025-03-26T16:26:47.051438image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length27
Mean length8.681551593
Min length3

Characters and Unicode

Total characters513644
Distinct characters33
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2085 ?
Unique (%)3.5%

Sample

1st rowtuberculosa
2nd rowimbricata
3rd rowconnectens
4th rowlaevis
5th rowbonachensis
ValueCountFrequency (%)
acutus 1105
 
1.8%
radiata 638
 
1.1%
bartonii 521
 
0.9%
gibbosus 501
 
0.8%
appressa 444
 
0.7%
modicella 437
 
0.7%
rusticus 389
 
0.6%
campanulata 379
 
0.6%
carinata 372
 
0.6%
minor 370
 
0.6%
Other values (6100) 54816
91.4%
2025-03-26T16:26:47.264454image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 74608
14.5%
i 56571
11.0%
s 47874
9.3%
e 37690
 
7.3%
n 37248
 
7.3%
r 32765
 
6.4%
u 31299
 
6.1%
t 28842
 
5.6%
l 28125
 
5.5%
c 26390
 
5.1%
Other values (23) 112232
21.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 513644
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 74608
14.5%
i 56571
11.0%
s 47874
9.3%
e 37690
 
7.3%
n 37248
 
7.3%
r 32765
 
6.4%
u 31299
 
6.1%
t 28842
 
5.6%
l 28125
 
5.5%
c 26390
 
5.1%
Other values (23) 112232
21.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 513644
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 74608
14.5%
i 56571
11.0%
s 47874
9.3%
e 37690
 
7.3%
n 37248
 
7.3%
r 32765
 
6.4%
u 31299
 
6.1%
t 28842
 
5.6%
l 28125
 
5.5%
c 26390
 
5.1%
Other values (23) 112232
21.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 513644
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 74608
14.5%
i 56571
11.0%
s 47874
9.3%
e 37690
 
7.3%
n 37248
 
7.3%
r 32765
 
6.4%
u 31299
 
6.1%
t 28842
 
5.6%
l 28125
 
5.5%
c 26390
 
5.1%
Other values (23) 112232
21.9%

taxonRank
Text

Missing 

Distinct2
Distinct (%)< 0.1%
Missing1867459
Missing (%)96.9%
Memory size14.7 MiB
2025-03-26T16:26:47.310616image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.999847883
Min length7

Characters and Unicode

Total characters591641
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowsubspecies
2nd rowsubspecies
3rd rowsubspecies
4th rowsubspecies
5th rowsubspecies
ValueCountFrequency (%)
subspecies 59162
> 99.9%
variety 3
 
< 0.1%
2025-03-26T16:26:47.394654image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 177486
30.0%
e 118327
20.0%
i 59165
 
10.0%
u 59162
 
10.0%
b 59162
 
10.0%
p 59162
 
10.0%
c 59162
 
10.0%
V 3
 
< 0.1%
a 3
 
< 0.1%
r 3
 
< 0.1%
Other values (2) 6
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 591641
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 177486
30.0%
e 118327
20.0%
i 59165
 
10.0%
u 59162
 
10.0%
b 59162
 
10.0%
p 59162
 
10.0%
c 59162
 
10.0%
V 3
 
< 0.1%
a 3
 
< 0.1%
r 3
 
< 0.1%
Other values (2) 6
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 591641
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 177486
30.0%
e 118327
20.0%
i 59165
 
10.0%
u 59162
 
10.0%
b 59162
 
10.0%
p 59162
 
10.0%
c 59162
 
10.0%
V 3
 
< 0.1%
a 3
 
< 0.1%
r 3
 
< 0.1%
Other values (2) 6
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 591641
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 177486
30.0%
e 118327
20.0%
i 59165
 
10.0%
u 59162
 
10.0%
b 59162
 
10.0%
p 59162
 
10.0%
c 59162
 
10.0%
V 3
 
< 0.1%
a 3
 
< 0.1%
r 3
 
< 0.1%
Other values (2) 6
 
< 0.1%
Distinct12118
Distinct (%)1.0%
Missing757161
Missing (%)39.3%
Memory size14.7 MiB
2025-03-26T16:26:47.520577image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length69
Median length47
Mean length8.788549958
Min length2

Characters and Unicode

Total characters10277884
Distinct characters88
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2540 ?
Unique (%)0.2%

Sample

1st rowBruguière
2nd row(Duchassaing)
3rd rowLutken
4th rowGaokoin
5th rowFisher
ValueCountFrequency (%)
98274
 
6.8%
linnaeus 78139
 
5.4%
say 43834
 
3.0%
lamarck 28284
 
1.9%
verrill 22068
 
1.5%
stimpson 21865
 
1.5%
gmelin 20027
 
1.4%
dall 17934
 
1.2%
sowerby 15894
 
1.1%
smith 15828
 
1.1%
Other values (7044) 1091982
75.1%
2025-03-26T16:26:47.740413image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 907174
 
8.8%
a 780906
 
7.6%
n 688521
 
6.7%
r 662129
 
6.4%
( 616320
 
6.0%
) 616320
 
6.0%
i 579400
 
5.6%
s 498870
 
4.9%
l 491585
 
4.8%
o 390791
 
3.8%
Other values (78) 4045868
39.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10277884
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 907174
 
8.8%
a 780906
 
7.6%
n 688521
 
6.7%
r 662129
 
6.4%
( 616320
 
6.0%
) 616320
 
6.0%
i 579400
 
5.6%
s 498870
 
4.9%
l 491585
 
4.8%
o 390791
 
3.8%
Other values (78) 4045868
39.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10277884
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 907174
 
8.8%
a 780906
 
7.6%
n 688521
 
6.7%
r 662129
 
6.4%
( 616320
 
6.0%
) 616320
 
6.0%
i 579400
 
5.6%
s 498870
 
4.9%
l 491585
 
4.8%
o 390791
 
3.8%
Other values (78) 4045868
39.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10277884
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 907174
 
8.8%
a 780906
 
7.6%
n 688521
 
6.7%
r 662129
 
6.4%
( 616320
 
6.0%
) 616320
 
6.0%
i 579400
 
5.6%
s 498870
 
4.9%
l 491585
 
4.8%
o 390791
 
3.8%
Other values (78) 4045868
39.4%